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This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

This paper aims to study the initial trust of the owner to the contractor, establish the initial trust mechanism, explore the factors that affect the initial trust of the owner to the contractor and analyze its influence mechanism. Based on this, it is easy for the owners and contractors to take targeted measures to improve the initial trust, which is conducive to the sustainable development of the project.

On the basis of reading a large amount of literature, this paper constructs the occurrence mechanism of the owner's initial trust to the contractor from the five factors of trust propensity, trust belief, trustee’s characteristics, institution-based trust, trust motivation and from the perspective of the owner using the structural equation model for questionnaire survey and empirical analysis.

The results of this paper show that the institution-based trust, the trustee’s characteristics and the trust belief of the trustor clearly have a positive effect on trust motivation, and the trustee’s characteristics have the most significant effect on the trust motivation. The influence of trust propensity on trust motivation was not significant.

This paper studies the occurrence mechanism of the owner's initial trust in the contractor, discusses its influencing factors and analyzes the influence of these factors on the initial trust, which enriches the theoretical system of initial trust research. The results of this study can help owners and contractors to develop targeted measures to build good initial trust.

Although trust is generally taken as a fundamental factor in influencing relational behavior in contractor–subcontractor collaboration, the determination of an optimal level of trust is still lacking. Trust with an optimal tipping point that matches dependence best is considered the optimal trust to improve relational behavior between general contractors and subcontractors. To fill the knowledge gap, this study explores how combinations of trust and dependence trigger relational behavior between general contractors and subcontractors through a configurational approach.

Questionnaires were administered to 228 middle management and technical staff members of the general contractor. The data were analyzed using fuzzy-set qualitative comparative analysis (fsQCA), and the inductive analytic method allowed researchers to explore configurations of different dimensions and levels of dependence and trust.

Necessity analysis results indicated that neither dependence nor trust was a necessary condition for facilitating relational behavior. Through sufficiency analysis, four configurations of optimal trust matched with dependence were identified in contractor–subcontractor collaboration. Even if contractors rely only on subcontractors for resources, the optimal trust between contractors and subcontractors should include both institution- and cognition-based trust. In the event that contractor–subcontractor collaboration involves relational dependence, both affect- and cognition-based trust are necessary for the optimal trust.

This study enhances existing research by delving deeper into a nuanced understanding of optimal trust in dependence scenarios, and enriches project governance theory by uncovering the internal transmission of relational governance. Practically, this study offers general contractors guidance on how to establish optimal trust strategies based on the dual dependence level with subcontractors, which can facilitate subcontractors' relational behavior, and ultimately improve contractor–subcontractor collaboration performance.

The authors study and compare the effects of three CEO compensation restricting policies issued by the Chinese government in 2009, 2012 and 2015. This paper aims to shed light on the conditions under which CEO compenstation can be effectively regulated without negatively affecting firm performance.

These policies targeted state-owned enterprises (SOEs), especially central state-owned enterprises (CSOEs). Using these policies as natural experiments, the authors investigate how their effects differ on CEO compensation, firm performance and two known performance-decreasing mechanisms: perk consumption and tunneling activities.

The authors show that restricting CEO pay does not necessarily backfire in terms of deteriorating firm performance. This non-decreasing firm performance can be achieved by restricting perk consumption and tunneling activities while introducing CEO pay regulations.

The authors exploit a powerful experimental setting in the context of China. The evidence contributes to the literature on CEO pay regulations and is relevant to the managerial decisions of policy makers and boards of directors.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

The use of social media is one of the new technological options that has been recommended as a potential new strategy for delivering high-quality, high-value cancer prevention and management services. Despite the increasing use of social media, little research has been done on the use of social media in brain tumors. Therefore, this systematic review aims to provide a comprehensive review of the use of social media in brain tumor research.

A systematic search was performed in PubMed, Scopus and Web of Science from inception to August 1, 2022. English full-text articles evaluating social media use, benefit or content in brain tumor were considered.

Sixteen documents satisfied the inclusion criteria and were included in the final analysis. Most of the included studies (n = 11/16) were conducted and published by researchers in the USA. In terms of social media platform, most studies focused on Twitter (8/16, 50%) and YouTube (8/16, 50%), followed by Facebook (6/16, 37.5%) and Instagram (4/16, 25%). Most studies (n = 7/12) analyzed the content of brain tumor information provided on social media, followed by patients’ use of social media (n = 3/12) and the quality of information on social media (n = 3/12). The other three articles also examined patient recruitment, crowdfunding and caregiver use of social media.

By identifying the use, benefits and content of social media platforms in different settings, patients, clinicians and policymakers can better benefit from harnessing the power of social media in different ways, leading to improved health-care services.

To the authors knowledge, this is the first study to systematically examine social media use, benefits and content status in brain tumors.

The preferences and adoption of recycled materials by consumers are subject to a variety of factors, such as enablers and barriers. Despite this, there exists a paucity of research concerning stakeholders' perceived value and real purchase decision towards recycled products. Consequently, this research study aims to fill this gap by investigating stakeholders' perceived value of recycled products derived from construction and demolition (C&D) waste and its effect on purchase decisions.

Research data were collected from 219 valid questionnaires completed by Chinese stakeholders. Structural equation modeling (SEM) was then employed to test eight hypotheses.

The results show intrinsic cue (materials) and extrinsic cue (brand) influence the stakeholders’ judgment on C&D waste recycled products’ value and then their purchase intention. However, cues such as quality, word-of-mouth, price, policy and advertised have not play a significant role in practice.

This research study verified the significance of brand and material cues on decision making for purchasing C&D waste recycled products, providing new insights to policy making to enhance the uptake of C&D waste recycled products in construction industry.

The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between principals and agents, to introduce strategies that embrace the social values, economic motivation and institutional designs historically adopted to curtail dishonest acts in international business and to inform an improved principal–agent theory that reflects principal–agent reciprocity as shaped by social, political, cultural, economic, strategic and ideological forces

The critical historical research method is used to analyze Chinese compradors and the foreign companies they served in pre-1949 China.

Business practitioners can extend orthodox principal–agent theory by scrutinizing the complex interactions between local agents and foreign companies. Instead of agents pursuing their economic interests exclusively, as posited by principal–agent theory, they also may pursue principal-shared interests (as suggested by stewardship theory) because of social norms and cultural values that can affect business-related choices and the social bonds built between principals and agents.

The behaviors of compradors and foreign companies in pre-1949 China suggest international business practices for shaping social bonds between principals and agents and foreign principals’ creative efforts to enhance shared interests with local agents.

Understanding principal–agent theory’s limitations can help international management scholars and practitioners mitigate transaction partners’ dishonest acts.

A critical historical analysis of intermediary businesspeople’s (mis)behavior in pre-1949 (1840–1949) China can inform the generalizability of principal–agent theory and contemporary business strategies for minimizing agents’ dishonest acts.

The aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.

The study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.

The study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.

The ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.

The study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.

The exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.

The purpose of this study is to explore how government subsidies influence technology innovation in new-energy enterprises in the new era of Industry 4.0. Specifically, this study investigates the mediating effect of digital transformation and the moderating effect of a top management team (TMT) with digital experience.

Using a sample of 225 listed new-energy companies, with annual information, patent data, and financial data for the years 2010–2020, this study employs panel fixed effect regression models to obtain the results.

This study finds strong evidence that government subsidies promote the technology innovation of new-energy enterprises, and digital transformation partially mediates the effect of government subsidies on technology innovation. In addition, a TMT's digital experience moderates the effect of government subsidies on digital transformation, but has no significant moderating effect on the relationship between digital transformation and technology innovation. Further analysis shows that subsidies make a sustained contribution to both digital transformation and technological innovation over the next two years. The digital subsidies have a stronger role in promoting digital transformation and further technological innovation through digital transformation.

The Chinese government needs to continue to intermittently increase subsidies for new-energy enterprises, and focus on guiding enterprises' digital transformation. Chinese new-energy enterprises should pay attention to the importance of having TMTs with digital experience, make full use of government subsidies, actively implement digital transformation, and improve their innovation levels.

A new conceptual framework is proposed to examine the relationships between government subsidies, digital transformation, a TMT's digital experience, and technology innovation. This paper provides an important theoretical basis and practical reference for improving the technology innovation ability of Chinese new-energy enterprises, and the high-quality development of renewable energy in the context of Industry 4.0.