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With the popularity of the internet and the increasing numbers of netizens, tremendous information flows are generated daily by the intelligently interconnected individuals. The diffusion processes of different information are not independent, and they interact with and influence each other. Modeling and analyzing the interaction between correlated information play an important role in the understanding of the characteristics of information dissemination and better control of the information flows. This paper aims to model the correlated information diffusion process over the crowd intelligence networks.

This study extends the classic epidemic susceptible–infectious–recovered (SIR) model and proposes the SIR mixture model to describe the diffusion process of two correlated pieces of information. The whole crowd is divided into different groups with respect to their forwarding state of the correlated information, and the transition rate between different groups shows the property of each piece of information and the influences between them.

The stable state of the SIR mixture model is analyzed through the linearization of the model, and the stable condition can be obtained. Real data are used to validate the SIR mixture model, and the detailed diffusion process of correlated information can be inferred by the analysis of the parameters learned through fitting the real data into the SIR mixture model.

The proposed SIR mixture model can be used to model the diffusion of correlated information and analyze the propagation process.

The primary purpose of this study is not only to examine the connections between self-determined motivation, attitudes toward change and participation in change, but also to explore the moderating impact of perceived organizational support on organizational change, and the mediating role of attitudes toward change in the link between perceived competence and participation in change.

The data were collected from one semiconductor manufacturing company (study 1) and one logistics service company (study 2). Employees who experienced organizational change before were invited to finish the survey. The partial least squares-structural equation modelling (PLS-SEM) technique and SPSS PROCESS (model 14) were utilized to analyze the data.

The study findings indicated that the perceived autonomy and relatedness were positively connected with perceived competence, which in turn would lead to better attitude toward change. Additionally, it was found that the perceived competence and attitude toward change would positively predict participation in change. More importantly, perceived organizational support would reinforce the positive relationship between attitude toward change and participation in change.

Although there are many organizational change reports, relatively little attention has been paid not only to the mediating role of attitudes toward change in the implication of organizational change but also to the moderating impact of perceived organizational support on the final success of organizational change.

: 本研究的主要目的, 除了探討自決動機和對變革的態度兩者與參與變革的關係;也探究組織支持感對組織變革所起的緩和作用, 以及對變革的態度在感知的才能和參與變革兩者的關聯上所起的調節作用。

: 有關的數據取自一間半導體製造商 (研究一) 和一間物流服務公司 (研究二) 。 曾體驗過組織變革的僱員被邀參與一項調查, 研究人員採用結構方程模式: 偏最小平方法 PLS-SEM、以及SPSS PROCESS (模型14), 來分析調查得來的數據。

: 研究結果顯示、感知的自主和關聯性兩者與感知的才能有正關聯的關係, 而這反過來則會引來對變革有較良好的態度。研究結果亦顯示、感知的才能和對變革的態度兩者均能積極預測變革的參與;更重要的是、組織支持感會強化對變革的態度與參與變革之間的正關聯。

: 雖然有關組織變革的研究報告唯數不少, 惟於組織變革上的啟示而言, 探討對變革的態度所起的調節作用的研究實唯數不多, 而且、探討組織支持感對組織變革能否最終成功所起的緩和作用的研究似頗稀少。

This paper aims to analyse the effects of events image from host communities’ perspective on the city’s overall image and the intention to recommend the events and the city as a tourism destination.

The research used a bivariate data analysis based on Spearman’s correlation and regression analysis to determine useful variables to predict the intention to recommend the city as a tourism destination. Data collection was face-to-face and online with a non-probabilistic sample of Viseu city residents, the second largest city in the central region of Portugal.

The findings had implications for researchers, governments and stakeholders. From the resident’s point of view, there is a high correlation between the overall city image and the intention to recommend it as a tourism destination. Event image and the intention to recommend the event participation affect the overall city image. Results point out the resident as natural promoters of events and their city if the local events have an appeal that generates their participation. Conclusions indicated that cities need to re-thinking tourism from the citizen’s perspective as staycation is a grown option.

Event image by host-city residents’ perceptions is an underdevelopment theme in the literature, although residents’ participation is essential to the success of most events. Local events can promote tourist citizenship and reinforce the positioning of tourism destinations, associating them with an image of desirable places to visit and live.

The aim of this paper is to examine how managerial ability affects corporate tax aggressiveness.

The study follows the work of Demerjian, Lev, and McVay (2012) and quantifies managerial ability by calculating how efficiently managers generate revenues from given economic resources using the data envelopment analysis (DEA) approach. The study uses a wide range of measures of tax aggressiveness. Firm fixed-effects regressions and a difference-in-differences approach using information regarding CEO turnover to control for endogeneity are used.

The study finds a negative relationship between managerial ability and corporate tax aggressiveness. Further tests show that this negative relationship is more pronounced for firms with higher investment opportunities or firms with more reputational concerns.

Given the significant costs associated with tax aggressiveness and the negative effect it can have on managerial reputation if discovered, the results suggest that more able managers invest less effort in aggressive tax avoidance activities. This study furthers the understanding of how managerial personal traits affect corporate decision-making.

This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.

This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.

To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.

The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.

This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.

This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.

The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change. Furthermore, a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability. Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method.

The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks. The proposed trajectory model could provide safety lane-change path planning, and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system.

This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles. There are two main contributions: the first is a more quantifiable trajectory model for self-driving articulated vehicles, which provides the opportunity to adapt vehicle and scene changes. The second involves designing a feedback linearization controller, combined with a multi-objective decision-making mode, to improve the comprehensive performance of intelligent vehicles. This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

The purpose of this study is to examine the potential of integrating material from the arts into postgraduate curricula to deepen students’ engagement with marketing phenomena. The authors assess the use of arts-based activities, within a broader critical pedagogy, for encouraging imaginative and analytical thinking.

The authors devised two learning activities and an interpretive method for studying their value. The activities were an individual essay connecting themes in song lyrics to marketing, and a group photography project. These were applied, within a broader, critical approach, in postgraduate modules on sustainability, ethics and critical marketing. Data collection comprised diaries kept by the teachers, open-ended feedback from students and students’ assignments.

Students showed high levels of engagement, reflexivity and depth of thought, in felt experiences of learning. Their ability to make connections not explicitly in the materials, and requiring imaginative jumps, was notable. Several reported lasting changes to their behaviour. Some found the tasks initially intimidating or, once they were more engaged, stressful or saddening.

This adds to scholarship on management education by showing the usefulness of an arts-based approach towards a transformative agenda.

It offers a template of how to draw from the arts to strengthen critical engagement upon which marketing teachers can build. It also contains practical advice on the challenges and benefits of doing so.

The authors provide evidence that this approach can enhance sensitivity and reflexivity in students, potentially producing more ethical and sustainable decisions in future.

The pedagogical interventions are novel and of value to lecturers seeking to enhance critical engagement with theory. An empirical study of an attempt to integrate arts into teaching marketing represents a promising direction, given the discipline’s creative nature.