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In large-scale group decision-making (LSGDM) situations, existing TODIM group decision-making methods often fail to account for the influence of social network relationships and the bounded rationality of decision-makers (DMs). To address this issue, a new TODIM-based group decision-making method is proposed that considers the current trust relationships among DMs in a large-scale trust relationship network.

This method consists of two main stages. In the first stage, the large-scale group is partitioned into several sub-clusters based on trust relationships among DMs. The dominance degree matrix of each sub-cluster is then aggregated into the large-scale group dominance degree. In the second stage, after aggregating the large-scale group dominance degree, the consensus index is calculated to identify any inconsistent sub-clusters. Feedback adjustments are made based on trust relationships until a consensus is reached. The TODIM method is then applied to calculate the corresponding ranking results. Finally, an illustrative example is applied to show the feasibility of the proposed model.

The proposed method is practical and effective which is verified by the real case study. By taking into account the trust relationships among DMs in the core process of LSGDM, it indeed has an impact on the decision outcomes. We also specifically address this issue in Chapter Five. The proposed method fully incorporates the bounded rationality of DMs, namely their tendency to accept the opinions of trusted experts, which aligns more with their psychology. The two-stage consensus model proposed in this paper effectively addresses the limitations of traditional assessment-based methods.

This study establishes a two-stage consensus model based on trust relationships among DMs, which can assist DMs in better understanding trust issues in complex decision-making, enhancing the accuracy and efficiency of decisions, and providing more scientific decision support for organizations such as businesses and governments.

The aim of this research is to examine the application of the stereotype content model (SCM) in the field of marketing from macro (the country of origin), meso- (corporate image) and micro (service providers, brands, advertising and promotions) levels.

This paper collects, reviews and summarizes the relevant literature, and prospects future research directions from three levels on this research topic.

First, the authors contend that competence primacy popularizes in the early work but warmth becomes more influential recently. Second, they identify and discuss two doubts of the SCM in marketing, namely the moral dimension and the link between brands as intentional agents framework (BIAF) and the brand personality theory. Finally, they suggest several research avenues for the use of SCM in marketing research, including research on nation branding, emerging global brands and Confucianist cultures at macro level, artificial intelligence and warmth-as-competence strategy at meso-level, and brand personality and the brand animal logo at micro level.

As an established framework in social psychology, the SCM has been increasingly applied in marketing research and a literature review in this light appears timely. This paper conducts for the first time a comprehensive review of the SCM in the marketing field on three levels, projects promising research directions, and thus contributes to the academia of marketing.

Drawing on the generativity framework, this study aims to investigate the relationship between the Dark Triad personalities (Machiavellianism, narcissism, and psychopathy) and knowledge hiding. This study also identifies the mediating role of generativity motivation and the moderating role of focus on opportunities.

Using a convenience sample, a two-wave time-lagged study collected survey responses from 498 employees from manufacturing industries in China, and the data was analyzed using hierarchal regression and bootstrapping methods.

This study found that Machiavellianism and psychopathy are both positively related to generativity motivation. The generativity motivation plays a mediating role in the paths of Machiavellianism and psychopathy on knowledge hiding, and a focus on opportunities positively moderates the direct and indirect effect of Machiavellianism and psychopathy on knowledge hiding.

Based on the generativity framework, we find a new underlying mechanism between the Dark Triad personalities and knowledge hiding, thereby further enriching the literature in relation to their influence over knowledge management. Moreover, it also finds that a focus on opportunities can weaken the negative relationships between the Dark Triad personalities and knowledge hiding.

This study draws on the trait activation theory to investigate the relationship between Machiavellianism and relational energy, considering the mediating role of facades of conformity and the moderating role of leader–member exchange ambivalence.

We collected survey data from 275 employees in central China at three time points. We conducted confirmatory factor analysis and bootstrapping to test the hypotheses using Mplus7.0 and the PROCESS macro.

We found that facades of conformity mediated the relationship between Machiavellianism and relational energy. Moreover, the indirect effect of Machiavellianism on relational energy via facades of conformity was more significant when leader–member exchange ambivalence is higher.

This study provides empirical evidence of how and when Machiavellians acquire relational energy from leaders.

Complexity is the main challenge for present and future manufacturers. Assembly complexity heavily affects a product’s final quality in the fully automated assembly system. This paper aims to propose a new method to assess the complexity of modern automated assembly system at the assembly design stage with respect to the characteristics of both manufacturing system and each single component to be mounted. Aiming at validating the predictive model, a regression model is additionally presented to estimate the statistic relationship between the real assembly defect rate and predicted complexity of the fully automated assembly system.

The research herein extends the S. N. Samy and H. A. ElMaraghy’s model and seeks to redefine the predictive model using fuzzy evaluation against a fully automated assembly process at the assembly design stages. As the evaluation based on the deterministic scale with accurate crisp number can hardly reflect the uncertainty of the judgement, fuzzy linguistic variables are used to measure the interaction among influence factors. A dependency matrix is proposed to estimate the assembly complexity with respect to the interactions between mechanic design, electric design and process factors and main functions of assembly system. Furthermore, a complexity attributes matrix of single part is presented, to map the relationship between all individual parts to be mounted and three major factors mentioned in the dependency matrix.

The new proposed model presents a formal quantification to predict assembly complexity. It clarifies that how the attributes of assembly system and product components complicate the assembly process and in turn influence the manufacturing performance. A center bolt valve in the camshaft of continue variable valve timing is used to demonstrate the application of the developed methodology in this study.

This paper presents a developed method, which can be used to improve the design solution of assembly concept and optimize the process flow with the least complexity.

The purpose of this study is to compare the thermal performance of two flow configurations in corrugated plate heat exchanger (CPHE): vertical flow configuration (CPHE_vert.) and diagonal flow configuration (CPHE_diag.). The study aims to determine the differences between these configurations and evaluate their respective thermal performance based on metrics such as heat transfer rates, pressure drop values and flow distribution.

The study compares the thermal performance of two flow arrangements of CPHE using identical geometrical dimensions and test conditions. Computational fluid dynamics (CFD) is employed, and a validated numerical model is used for the investigation. The comparison is based on analyzing the rate of heat transfer and pressure drop data between the two flow arrangements.

The findings indicate that the diagonal flow configuration in CPHEs offers improved flow distribution, enhanced heat transfer performance and lower pressure drop compared to the vertical flow configuration. However, the differences in general in the thermal performance of CPHE_vert. and CPHE_diag. are found to be minimal.

To the best of the author’s knowledge, this study represents the first attempt to investigate the impact of vertical and diagonal flow configurations on the thermal performance of the CPHE.