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The purpose of this paper is to derive the relationship between color schemes and emotion to serve for designers and consumers.

The three attributes of hue, brightness and saturation of the selected sample color are analyzed, and the Semantic Differential (SD) method is used for the emotional evaluation of color schemes, and data obtained from the emotional evaluation of color schemes is analyzed by using Excel software for mean statistics and SPSS software for factor analysis and cluster analysis.

From the results of the factor analysis, three main factors that affect the feeling of the color scheme can be extracted: “personality”, “gender” and “fashion”. Color emotions can be achieved by changing the level of color saturation and brightness, the cold and warmth of the hue and the way of color combination.

Since it takes a long time to fill out the questionnaire, the number of valid questionnaires collected is a little less and the research data is limited. In addition, some problems are not taken into account such as geography and so on, so the results of the statistical analysis are not very precise and further research is needed.

It can provide information of emotional color schemes for designers and consumers, and based on the SD method, an emotional color matching questionnaire is designed and statistical analysis is conducted to establish the relationship between emotion and color schemes.

Based on the fashion color sample and color harmony theory, the color matching rules and color matching schemes are designed independently.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

Inter-organizational collaboration is the organizational guarantee and key link to achieve the goals of megaproject management. Project governance has always played an important role in the construction of megaprojects, but the relationship between project governance and organizational collaboration is unclear. The purpose of this study is to explore the role paths of different project governance mechanisms in influencing the collaborative behaviors of stakeholders and collaborative performance and to elucidate the mechanism of project governance on inter-organizational collaboration.

A conceptual framework was developed based on a comprehensive literature review, termed the structural equation model (SEM). The hypotheses of the model were tested based on data obtained from a questionnaire survey of 235 experts with experience in megaprojects within the construction industry in China.

The results show that project governance positively contributes to the collaborative behavior of megaproject stakeholders and the collaborative performance of the project team. Collaborative behavior acts as a partial mediator between project governance and the collaborative performance of the megaproject inter-organization alliance. The complexity of the project modulates the relationship between the governance mechanism of the project and the collaborative behavior of the stakeholders, which affects the collaborative performance of the megaproject inter-organization alliance.

The findings provide theoretical and practical implications for promoting positive collaborative behavior among stakeholders in megaproject selection and improving the collaborative performance of megaproject inter-organization alliances.

This study aims to examine whether corporate stconcerns on social responsibility issues pressurize corporate managers to act in a socially responsible way and how this affects corporate value.

This study follows previous studies such as Wu et al. (2008) and Jiang and Huang (2011) in using the research model.

The analysis shows that in regions where large attention paid to demolitions, corporate managers are under great pressure from corporate stakeholders and they thus act in more socially responsible ways; this, in turn, results in higher corporate values. Furthermore, in regions in which demolition events attract more attention, the increase in corporate value is relatively small for state-owned enterprises and unprofitable listed enterprises.

The findings demonstrate that internet governance heightens corporate stakeholders’ awareness of social responsibility, and this leads to pressure on corporate relative behaviors to satisfy the requests of corporate stakeholders, leading to an increase in corporate value and improvement in social welfare.

Given the socialisation of men and women to their gender roles and expression of emotion, this study aims to investigate whether there are gender differences in the use of emotive language in electronic word-of-mouth (eWOM), specifically in online reviews. The authors propose that female reviewers will use strong emotive terms, such as love, more frequently in online reviews than do male reviewers. The authors further propose that the gender of the reviewer influences audience responses to the reviewer’s use of emotive terms in online reviews.

The authors conducted secondary data analysis of restaurant reviews (Study 1) to provide evidence on whether the gender of the reviewer affects the frequency of use of emotive terms in an online review. In addition, three separate experiments (Studies 2–4) were conducted to test the theoretical arguments.

The results of the secondary data analysis indicated that female online reviewers used the term “love” much more frequently in their reviews than male reviewers, whereas there was no usage difference for the term “like”. The experimental studies further showed that an emotive review by a male reviewer containing the word “love” resulted in a higher evaluation of the restaurant being reviewed than a non-emotive review containing the word “like”. This difference was stronger when the overall rating was less salient and for consumers who believe (vs do not believe) that men and women use emotional language differently.

First, the paper extends our understanding of gender differences in emotional expression within the domain of eWOM and online reviews as well as our understanding of consumer responses to these gender differences. Second, the authors identify a boundary condition for these gender effects, namely, the overall rating score. Third, the authors find that consumer beliefs regarding gender stereotypes in emotional expression provide an explanation for these effects.

The results of the research indicate that the electronic algorithms operating on review sites might be modified in terms of their criteria for selecting the reviews to display to consumers, as consumer decision-makers may find greater utility in reviews written by male reviewers that contain strongly positive emotive terms.

The research extends the knowledge on gender differences in emotional expression in online reviews by demonstrating the actual usage patterns and differing responses to the emotional expressions of each gender.

The purpose of this paper is to develop a novel multivariate fractional grey model termed GM(a, n) based on the classical GM(1, n) model. The new model can provide accurate prediction with more freedom, and enrich the content of grey theory.

The GM(α, n) model is systematically studied by using the grey modelling technique and the forward difference method. The optimal fractional order a is computed by the genetic algorithm. Meanwhile, a stochastic testing scheme is presented to verify the accuracy of the new GM(a, n) model.

The recursive expressions of the time response function and the restored values of the presented model are deduced. The GM(1, n), GM(a, 1) and GM(1, 1) models are special cases of the model. Computational results illustrate that the GM(a, n) model provides accurate prediction.

The GM(a, n) model is used to predict China’s total energy consumption with the raw data from 2006 to 2016. The superiority of the GM(a, n) model is more freedom and better modelling by fractional derivative, which implies its high potential to be used in energy field.

It is the first time to investigate the multivariate fractional grey GM(α, n) model, apply it to study the effects of China’s economic growth and urbanization on energy consumption.

The purpose of this paper is to study a fractional grey model FAGM(1,1,t^α) based on the GM(1,1,t^α) model and the fractional accumulated generating operation, and then predict the national health expenditure, the government health expenditure and the out-of-pocket health expenditure of China.

The presented univariate grey model is systematically studied by using the grey modelling technique, the fractional accumulated generating operation and the trapezoid approximation formula of definite integral. The optimal system parameters r and α are evaluated by the particle swarm optimisation algorithm.

The expressions of the time response function and the restored values of this model are derived. The GM(1,1), NGM(1,1,k,c) and GM(1,1,t^α) models are particular cases of the FAGM(1,1,t^α) model with deterministic r and α. Compared with other forecasting models, the results of the FAGM(1,1,t^α) model have higher precision.

The superiority of the new model has high potential to be used in the medicine and health fields and others. Results can provide a guideline for government decision making.

The univariate fractional grey model FAGM (1,1,t^α) successfully studies the China’s health expenditure.

This paper aims to explain how contractual complexity, including contractual control, coordination and adaptation, makes a difference to the task and relationship conflict, and then, to investigate the moderating roles played by both, total interdependence and interdependence asymmetry, in altering the association between the two types of conflicts.

This study obtained data through a questionnaire survey in the Chinese construction industry and the final sample consisted of 232 responses. The data were analysed using hierarchy analysis using SPSS.

The results are as follows: first, higher contractual control and coordination reduce the level of relationship conflicts, and higher contractual coordination also reduces the level of task conflicts; second, task conflict positively affects relationship conflict; third, task conflict mediates the relationship between contractual coordination and relationship conflict; and finally, when total interdependence is higher, task conflict induces more relationship conflict. On the contrary, high interdependence asymmetry weakens the positive relationship between task and relationship conflicts.

This study highlights the importance of contracts in conflict management. The findings can guide practitioners in drafting suitable contracts to deal with task and relationship conflicts more effectively.

This study differentiates the effects of distinct components of contracts on task and relationship conflicts, and then reveals the contingent effects of interdependence on the relationship between task and relationship conflicts in inter-organisational transactions.

This study aims to analyze the differences of electrocardiograph (ECG) characteristics for female drivers in calm and anxious states during driving.

The authors used various materials (e.g. visual materials, auditory materials and olfactory materials) to induce drivers’ mood states (calm and anxious), and then conducted the real driving experiments and driving simulations to collect driver’s ECG signal dynamic data. Physiological changes in ECG during the stimulus process were recorded using PSYLAB software. The paired T-test analysis was conducted to determine if there is a significant difference in driver’s ECG characteristics between calm and anxious states during driving.

The results show significant differences in the characteristic parameters of female driver’s ECG signals, including (average heart rate), (atrioventricular interval), (percentage of NN intervals > 50ms), (R wave average peak), (Root mean square of successive), (Q wave average peak) and ( S wave average peak), in time domain, frequency domain and waveform in emotional states of calmness and anxiety.

Findings of this work show that ECG can be used to identify driver’s anxious and calm states during driving. It can be used for the development of personalized driver assistance system and driver warning system.

Only a few attempts have been made on the influence of human emotions on physiological signals in the transportation field. Hence, there is a need for transport scholars to begin to identify driver’s ECG characteristics under different emotional states. This study will analyze the differences of ECG characteristics for female drivers in calm and anxious states during driving to provide a theoretical basis for developing the intelligent and connected vehicles.

Greenhouse gas (GHG) emission has a detrimental impact on climate change. There is an increasing trend for firms to use disclosure to signal stakeholders about its environmental responsibilities and performance in dealing with climate change. China is one of the countries producing the most carbon emissions. Over the last decade, Chinese state-owned enterprises (SOEs) are becoming important players in international trade. However, the existing literature provides limited evidence on how Chinese SOEs influence GHG disclosure. Through the lens of stakeholder–agency theory, this chapter studies the top 300 listed firms to examine the relationship between Chinese SOEs and the likelihood of GHG disclosure. The result suggests a negative relationship between Chinese SOEs and the likelihood of GHG disclosure. This could be explained as a consequence of the managers' political self-interests, economic and policy-oriented decision-making process and the power differentials between the government and SOE managers. This research extends the GHG literature to Chinese SOEs context, providing direct evidence on how state ownership impacts on GHG disclosure.