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The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

This study aims to explore the overall relationship between a boundary spanner and a partner firm, i.e. boundary spanner closeness to partner firm. Drawing on consumer-service provider relationship literature and the tripartite model of affect-behavior-cognition, the authors identify three key dimensions of such closeness, namely, boundary spanners’ relational ties, customer-specific capabilities and accommodative behaviors, and examine their effects on exchange outcomes in turbulent versus stable environments.

The paper examines the effects of three dimensions of boundary spanner closeness on various exchange outcomes (i.e. retailers’ cooperation, satisfaction and willingness for investment) using two industries as exemplars, characterized by distinct levels of environmental turbulence – the retailing networks of a major cell phone company and a petroleum company in China.

The results indicate that the three dimensions individually and jointly affect exchange outcomes and the interplay of customer-specific capabilities and relational ties affect exchange outcomes differently across industry turbulence.

The existing literature lacks a comprehensive understanding of the function of boundary spanners, which serve as a key relational interorganizational governance component. By identifying three key dimensions of boundary spanner closeness and examining their effectiveness in promoting exchange outcomes, this study advances the understanding of the role of boundary spanners in interorganizational governance.

The obtained simulation structures could reflect the appearances and the features of the fabrics. The purpose of this paper is to promote a lot for design and manufacturing of weft-knitted lace fabrics (WKLF).

The advantages of WKLF compared with warp-knitted ones were displayed. The formation mechanism of the WKLF was analyzed with employing the mechanics principles. Spring-mass model was proposed in this paper to achieve the simulation of the fabrics. End mass points and intermediate mass points were involved in the model. The displacement of end mass points was considered the dominance and the foundation to settle the positions of all the mass points.

A novel jacquard lace style fabric with pattern-background effect knitted on circular knitting machine were put forward, which were different from the traditional lace fabrics manufactured on the warp knitting machines.

First, as the manufacturing equipment, circular knitting machine costs much less than warp knitting machine; second, the elastic performance along weft direction of WKLF is more excellent than that of warp-knitted ones. Third, the excellent extensibility gives nice comfort; furthermore, long floating threads do not exist on the WKLF surface, so that the snag will be avoided.

In certain latitude areas, fruit growth is determined by the slope between 5° and 20°. According to the designed sunny slope direction and the parallel lines to the slope direction, we take two adjacent rows of the hedge to meet certain condition of the sun light, and draft the chart of shadow top contour based on the solar azimuth angle A and the coefficient of shadow length γ to get crown space of the rectangular cross section in different ground of slopes. Then, the crown section lateral is changed to get mathematical models which determine the crown space of different cross sections in hedgerow orchard.

In the hedgerow orchard of hilly land, the crown height changes with ground slope so as to meet the condition of the sun light. Using astronomical trigonometric formulas, this paper calculates solar position of the 40° north latitude in vernal equinox and autumnal equinox. At the same time, it calculates the shadow length of tree body, determines the shadow length coefficient y and drafts the chart of shadow top contour based on the solar azimuth angle A and the coefficient of shadow length γ. According to the design of the north-south direction, we take two lines of the hedge with the changing figure of the top contour of shadow and crown cross-section to get mathematical models which determine the crown height of different sections in different ground slope.

This study aims to put forward a theory for the design of the crown sections in hedgerow orchards.

The fruit trees located at the north latitudes 0°-60° were selected for analysis. In detail, the study period focused on the fruit trees’ growing season, that is from the vernal equinox to the autumnal equinox. Certain fixed hedge-shaped angle with sufficient sunlight throughout the seasons was calculated under the condition of the lines from north to south. Meanwhile, the crown cross section perpendicular to the lines was analyzed in rectangular, trapezoidal and triangular forms.

Results showed that the adaptive geographic latitudes to different crown sections should be determined by the ratio analysis between various crown heights and spans.

The optimum parameters of the crown sections in different latitude areas can be determined by the theory proposed in this study.

The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.

A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.

The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.

This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.

Trust is the glue that holds cooperative relationships together and often exists in an asymmetric manner. The purpose of this study is to explore how to mitigate the issue of losses or increased transaction costs caused by opportunistic behavior in a soft environment where trust asymmetry is quite common and difficult to avoid.

This study focuses on examining asymmetric trust between the government and the private sector in public-private partnership (PPP) projects. Drawing upon both project realities and relevant literature, the primary conditional variables influencing asymmetric trust are identified. These variables encompass power perception asymmetry, information asymmetry, interaction behavior, risk perception differences and government-side control. Subsequently, through the use of a survey questionnaire, binary-matched data from both the government and the private sector are collected. The study employs fuzzy-set qualitative comparative analysis (fsQCA) to conduct a configurational analysis, aiming to investigate the causal pathways that trigger asymmetric trust.

No single conditional variable is a necessary condition for the emergence of trust asymmetry. The pathways leading to a high degree of trust asymmetry can be categorized into two types: those dominated by power perception and those involving a combination of multiple factors. Differences in power perception play a crucial role in the occurrence of high trust asymmetry, yet the influence of other conditional variables in triggering trust asymmetry should not be overlooked.

The findings can contribute to advancing the study of trust relationships in the field of Chinese PPP projects. Furthermore, they hold practical value in facilitating the enhancement of trust relationships between the government and the private sector.

In an online shopping environment, individual reviews and aggregated ratings are important anchors for consumers’ purchasing decisions. However, few studies have considered the influence of aggregated ratings on consumer decision-making, especially at the neural level. This study aims to bridge this gap by investigating the consumer decision-making mechanism based on aggregated ratings to uncover the underlying neural basis and psychological processing.

An event-related potential experiment was designed to acquire consumers’ electrophysiological records and behavioral data during their decision-making processes based on aggregated ratings. The authors speculate that during this process, review valence categorization (RVC) processing occurs, which is indicated by late positive potential (LPP) components.

Results show that LPP components were elicited successfully, and perceptual review valence can modulate its amplitudes (one-star [negative] and five-star [positive] ratings evoke larger LPP amplitudes than three-star [neutral] ratings). The electroencephalogram data indicate that consumer decision-making processes based on aggregated ratings include an RVC process, and behavioral data show that easier review valence perception makes the purchase decision-making easier.

This study enriches the extant literature on the impact of aggregated ratings on consumer decision-making. It helps understand how aggregated ratings affect consumers’ online shopping decisions, having significant management implications. Moreover, it shows that LPP components can be potentially used by researchers and companies to evaluate and analyze consumer emotion and categorization processing, serving as an important objective physiological indicator of consumer behavior.

The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.

In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.

The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.

The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.

The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.