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Consistency and consensus are two important research issues in group decision-making (GDM). Considering some drawbacks associated with these two issues in existing GDM methods with intuitionistic multiplicative preference relations (IMPRs), a new GDM method with complete IMPRs (CIMPRs) and incomplete IMPRs (ICIMPRs) is proposed in this paper.

A mathematically programming model is constructed to judge the consistency of CIMPRs. For the unacceptably consistent CIMPRs, a consistency-driven optimization model is constructed to improve the consistency level. Meanwhile, a consistency-driven optimization model is constructed to supplement the missing values and improve the consistency level of the ICIMPRs. As to GDM with CIMPRs, first, a mathematically programming model is built to obtain the experts' weights, after that a consensus-driven optimization model is constructed to improve the consensus level of CIMPRs, and finally, the group priority weights of alternatives are obtained by an intuitionistic fuzzy programming model.

The case analysis of the international exchange doctoral student selection problem shows the effectiveness and applicability of this GDM method with CIMPRs and ICIMPRs.

First, a novel consistency definition of CIMPRs is presented. Then, a consistency-driven optimization model is constructed, which supplements the missing values and improves the consistency level of ICIMPRs simultaneously. Therefore, this model greatly improves the efficiency of consistency improving. Experts' weights determination method considering the subjective and objective information is proposed. The priority weights of alternatives are determined by an intuitionistic fuzzy (IF) programming model considering the risk preference of experts, so the method determining priority weights is more flexible and agile. Based on the above theoretical basis, a new GDM method with CIMPRs and ICIMPRs is proposed in this paper.

The purpose of this study is to examine how social ties (i.e. business ties and political ties) affect the adoption of green innovation in the context of emerging economies, separately and comparatively. In addition, this study also seeks to examine how absorptive capacity shapes the relationships between social ties and the adoption of green innovation.

A theoretical model with hypothesized relationships is proposed and tested using regression in SPSS. This study’s sample consists of a dataset covering 272 Chinese firms (based on a total of 544 respondents) operating in various industries with two key informants in each firm.

The authors find that business ties and political ties both facilitate the adoption of green innovation, whereas business ties influence the adoption more strongly than political ties do. This study’s findings also show that absorptive capacity strengthens the positive relationships between the two types of social ties and the adoption of green innovation.

Although scholarship has amply documented the role that social ties play in influencing corporate performance, few studies have considered how and under what conditions these ties can impact the adoption of green innovation. Overall, the authors add value to the environmental management and social capital literature by providing novel insights into the differential roles that business ties and political ties play in the adoption of green innovation under the influence of absorptive capacity.

Livestreaming, as a relatively new online marketing model, has generated numerous business opportunities for e-commerce and social commerce. The purpose of this paper is to investigate to what degree livestreaming content impacts online users' cognitive and emotional reactions and whether their cognitive and emotional responses affect their purchase intention.

Through the lens of regulatory focus theory (RFT) and stimulus–organism–response (S–O–R) theory, the authors empirically examine the influencing mechanisms of livestreaming on online consumers' purchase intentions. Structural equation models are used to analyze the relationships in the proposed research model.

The results of this study show that information-task fit positively affects consumers' perceived usefulness of livestreaming. Both visual effects and sociability positively affect consumers' perceived value and social presence. Furthermore, perceived usefulness and perceived joy positively affect consumers' purchase intentions in a livestreaming environment. This study’s results also demonstrate that the regulatory focus of consumers has a moderating effect on the influence of their perceived joy on shopping intentions.

This study contributes to the relevant literature by simultaneously examining the role of e-commerce platform characteristics and online consumer psychology in influencing behavioral intention. With a better understanding of their role, platform operators and sellers can refine their livestreaming marketing tools and strategies. Highlighting the interplays among external stimuli, user reactions and user motivational styles, this study contributes to mobile e-commerce literature and the broader literature on digital marketing and human–computer interaction.

The aim of this study is to investigate the impact of local political uncertainty on the asymmetric cost behavior (i.e. cost stickiness) for listed firms in China.

In this study, the authors manually collect the turnover data of prefecture-city officials as a measure of exogenous fluctuations in political uncertainty and obtain firm-level financial information from the China Stock Market Accounting Research (CSMAR) database. To perform the analysis, the authors augment the traditional cost stickiness model by including the interaction terms of the prefecture-city official turnover, and firm-level and prefecture-city level control variables.

The authors find that political turnover leads to a higher degree of cost stickiness, implying that firms retain slack resources when political uncertainty is high. Moreover, the effect of political turnover on cost stickiness is more pronounced for firms residing in regions with weaker institutional environments, and firms that are privately owned and with smaller size. The authors further provide evidence that policy uncertainty and the threat of losing political connection are two underlying channels. Overall, this study documents that the local political process is an important channel that influences corporate operational decisions.

This study provides the first piece of evidence on the relation between political uncertainty and cost stickiness at the local government level. Moreover, the authors propose and demonstrate two underlying channels through which political uncertainty affects firms' asymmetric cost behavior.

Fluctuations in the tender price index have an adverse effect on the construction sector and the economy at large. This is largely due to the positive relationship that exists between the construction industry and economic growth. The consequences of these variations include cost overruns and schedule delays, among others. An accurate forecast of the tender price index is good for controlling the uncertainty associated with its variation. In the present study, the efficacy of using an adaptive neuro-fuzzy inference system (ANFIS) for tender price forecasting is investigated. In addition, the Box–Jenkins model, which is considered a benchmark technique, was used to evaluate the performance of the ANFIS model. The results demonstrate that the ANFIS model is superior to the Box–Jenkins model in terms of the accuracy and reliability of the forecast. The ANFIS could provide an accurate and reliable forecast of the tender price index in the medium term (i.e. over a three-year period). This chapter provides evidence of the advantages of applying nonlinear modelling techniques (such as the ANFIS) to tender price index forecasting. Although the proposed ANFIS model is applied to the tender price index in this study, it can also be applied to a wider range of problems in the field of construction engineering and management.

Research on the effect of executive equity incentives is equivocal. Based on agency theory, some scholars take the convergence of interest logic to highlight the benefits of executive equity incentives. In contrast, others adopt the entrenchment logic to emphasize the increased agency costs. This study attempts to reconcile the debate on executive equity incentives and integrates the opposing views to unveil how executive equity incentives impact corporate social responsibility (CSR) performance.

Using the panel dataset of Chinese A-share listed firms from 2006 to 2022, this study integrates the convergence of interest and entrenchment logic to examine how executive equity incentives affect CSR performance.

We find that the relationship between executive equity incentives and CSR performance follows an inverted U-shaped form. According to the convergence of interest logic, executive equity incentives reduce agency costs when allocating resources to engage in CSR activities and enable firms to increase their CSR investments, ultimately realizing increased CSR performance. After a threshold, however, the accumulation of extensive equity incentives causes the entrenchment effect, resulting in declined CSR performance. Our empirical results also shed new light on its contingent perspective – the inverted U-shaped relationship is attenuated when firms’ stock liquidity is high.

This study attempts to reconcile the debate on executive equity incentives and integrates the opposing views to unveil the inverted U-shaped relationship between executive equity incentives and CSR performance. Our study opens promising avenues for further research on corporate governance and CSR strategies.

Lattice Boltzmann method (LBM) is employed to explore friction factor of single-phase fluid flow through porous media and the effects of local porous structure including geometry of grains in porous media and specific surface of porous media on two-phase flow dynamic behavior, phase distribution and relative permeability. The paper aims to discuss this issue.

The 3D single-phase LBM model and the 2D multi-component multi-phase Shan-Chen LBM model (S-C model) are developed for fluid flow through porous media. For the solid site, the bounce back scheme is used with non-slip boundary condition.

The predicted friction factor for single-phase fluid flow agrees well with experimental data and the well-known correlation. Compared with porous media with square grains, the two-phase fluids in porous media with circle grains are more connected and continuous, and consequently the relative permeability is higher. As for the factor of specific porous media surface, the relative permeability of wetting fluids varies a little in two systems with different specific surface areas. In addition, the relative permeability of non-wetting fluid decreases with the increasing of specific surface of porous media due to the large flow resistance.

Fluid-fluid interaction and fluid-solid interaction in the SC LBM model are presented, and schemes to obtain immiscible two-phase flow and different contact angles are discussed. Two-off mechanisms acting on the wetting fluids is proposed to illustrate the relative permeability of wetting fluids varies a little in two systems with different specific surface.

By reviewing the literature, this paper explores the current priorities and future directions of alliance post-formation dynamics research.

This paper collects and analyzes empirical studies on alliance post-formation dynamics that were published between 1990 and 2021.

Current research on alliance post-formation dynamics can be structured as antecedents and outcomes of dynamics and their moderating effects. Among these topics, antecedents of dynamics have been addressed in a large body of research encompassing diverse theoretical mechanisms and levels of analysis. However, there remain debates regarding the outcomes of alliances post-formation dynamics.

First, this paper enriches the theoretical plurality of the field by integrating the antecedents and outcomes of dynamics and their moderating effects. Second, this paper proposes a new scholarly perspective – “alliance dynamic capabilities” – to address the “disruption vs adaption” debates regarding the outcomes of alliance post-formation dynamics in current research. Third, this paper presents several promising future research directions with the aim to advancing the literature on alliance post-formation dynamics.

The main purposes of this research are: first of all, to re-classify the types of corporate social responsibility (CSR) into primary stakeholder-oriented CSR and secondary stakeholder-oriented CSR from the perspective of stakeholders and, second, to investigate empirically how and which types of CSR can better impact employees' job satisfaction and happiness management.

An online self-administered questionnaire was adopted to test the conceptual model. Questionnaires were sent to Chinese employees and restrict the data to those whose companies had experience implementing CSR. The study employed the partial least squares structural equation modeling (PLS-SEM) technique for data analysis using SmartPLS 4.0 software.

For factors of happiness management, both primary stakeholder-oriented CSR and secondary stakeholder-oriented CSR had significant and positive effects on happiness management. In addition, both primary and secondary stakeholder-oriented CSR positively and significantly affected job satisfaction, with primary stakeholder-oriented CSR way larger than secondary stakeholder-oriented CSR. Job satisfaction, in turn, was positively and significantly associated with happiness management. The results showed that the control variables of gender and education background had significant effects on happiness management.

First, the results provide useful empirical evidence in support of the feasibility that firms could develop competitive and sustainable development strategies by paying more attention to CSR practices. In terms of the primary stakeholder-oriented CSR, managers are recommended to put employees' benefits as a priority and invest in the to offer a healthy and safe working environment or employee support programs. In terms of the secondary stakeholder-oriented CSR, managers are suggested to denote parts of earnings to charity and to people in need. Second, in order to create job satisfaction, firms should put a stronger emphasis on CSR practices. When considering job satisfaction, managers should treat their employees in a socially responsible way and fulfill their demands and rights and place this at the core of their CSR activities.

First, this study makes a contribution to the existing literature by classifying the four important CSR practices into two types from the perspective of stakeholder theory. By incorporating a series of CSR practices and the stakeholder theory, this study provides a comprehensive and reasonable CSR classification, which has not been considered by prior research. Second, this study adds to the literature by defining the construct of happiness management explicitly along with identifying the dimensions of happiness management. Third, to the best of the authors' knowledge, this is one of the first studies exploring the relationship between CSR and happiness management. Finally, this study is among the first to investigate the correlation between job satisfaction and happiness management.

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China.

This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen.

The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications.

This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.