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The aim of this research is to explore the behavioral model of Chinese organizational leaders acquiring resources for the development of their organizations under the influence of hierarchically oriented social governance.

The paper compares the differences between Western and Chinese contexts and conducts a grounded multi-case study to explore leadership behavioral model in the Chinese context.

First, the Chinese social governance structure is hierarchically oriented, whereas the Western social governance structure is market oriented. Second, this unique inconformity found in the Chinese organizational leaders as contorted leadership, which refers to the inconsistency between leaders’ cognition and their behavior when acquiring resources for the development of their organizations, is defined. Third, the conflict between leaders’ cognition and behaviors is caused by the social governance mechanism within which leaders are embedded.

The authors have just made a first step to understand contorted leadership in the Chinese context, further researches should pay more attention to exploring the origins, functions and impacts of leaders’ contorted behaviors.

First, leadership is linked with social governance by emphasizing on the core role of social governance in allocating the resources which organizational leaders scramble for. Second, a new kind of leadership –contorted leadership – in the Chinese context that emphasizes on the contradiction between leaders’ cognition and behavior, which deepens the understanding of leadership contextualization, is identified.

The purpose of this paper is to study the wear evolution of metro wheels under the conditions of different track sequences, track composition and vehicle load and then to predict wheel wear and to guide its maintenance.

By using the SIMPACK and MATLAB software, numerical simulation analysis of metro wheel wear is carried out based on Hertz theory, the FASTSIM algorithm and the Archard model. First of all, the vehicle dynamics model is established to calculate the motion relationship and external forces of wheel-rail in the SIMPACK software. Then, the normal force of wheel-rail is solved based on Hertz theory, and the tangential force of wheel-rail is calculated based on the FASTSIM algorithm through the MATLAB software. Next, in the MATLAB software, the wheel wear is calculated based on the Archard model, and a new wheel profile is obtained. Finally, the new wheel profile is re-input into the vehicle system dynamics model in the SIMPACK software to carry out cyclic calculation of wear.

The results show that the setting order of different curves has an obvious influence on wear when the proportion of the straight track and the curve is fixed. With the increase in running mileage, the severe wear zone is shifted from tread to flange root under the condition of the sequence-type track, but the wheel wear distribution is basically stable for the unit-type track, and their wear growth rates become closer. In the tracks with different straight-curved ratio, the more proportion the curved tracks occupy, the closer the severe wear zone is shifted to flange root. At the same time, an increase in weight of the vehicle load will aggravate the wheel wear, but it will not change the distribution of wheel wear. Compared with the measured data of one city B type metro in China, the numerical simulation results of wheel wear are nearly the same with the measured data.

These results will be helpful for metro tracks planning and can predict the trend of wheel wear, which has significant importance for the vehicle to do the repair operation. At the same time, the security risks of the vehicle are decreased economically and effectively.

At present, many scholars have studied the influence of metro tracks on wheel wear, but mainly focused on a straight line or a certain radius curve and neglected the influence of track sequence and track composition. This study is the first to examine the influence of track sequence on metro wheel wear by comparing the sequence-type track and unit-type track. The results show that the track sequence has a great influence on the wear distribution. At the same time, the influence of track composition on wheel wear is studied by comparing different straight-curve ratio tracks; therefore, wheel wear can be predicted integrally under different track conditions.

The purpose of this paper is to investigate the temperature reliability for a parallel high-efficiency class-E power amplifier (PA).

To explore the relationship between temperature and direct current (DC) characteristics, output power, S parameters and efficiency of the PA quantitatively, a series of reliability experiments have been designed and conducted to study the temperature reliability for this PA.

From the results, the prominent performance degradation even failure is found during the testing. Furthermore, the thermal shock test can cause permanent failure, which is a great threat for PA.

Therefore, to ensure the good performance, the influence of temperature on PA reliability should be carefully considered during the stage of PA design.

All these can provide important guidance for the reliability design of PA.

All these can give some important guidance for PA application.

In addition, PA is usually designed according to the electrical properties at the room temperature. From the results above, it can be concluded that it may be unable to satisfy the performance requirement at high temperature. In turn, if it is designed according to the electrical properties at low temperature, the transistor often works in the super-saturated state, the reliability of PA will become the new problem. Therefore, to ensure the good performance, the influence of temperature on PA reliability should be carefully considered during the design.

Introduction The transformation function for two‐sector production models has been used extensively in the international trade and general equilibrium literature. It has been derived both graphically and mathematically from individual sector production functions that are assumed to be linearly homogeneous. The result has been a convex set possessing first derivatives that have frequently been used. However, there seems to be a lack of research on further properties attributable to the transformation function. The purpose of this paper is to analyze these additional properties. We begin by proving that the transformation function is linearly homogeneous in all of its arguments. We then derive the standard first derivatives of the transformation function providing their usual economic interpretation. Finally, we conclude by deriving and interpreting the second‐order derivatives of the transformation function.

Broiler meat is the most commonly used meat product worldwide. Although China is regarded as one of the three largest broiler producers, the per capita chicken consumption remains low. Consumers' cognitive bias and the information acquisition channels are believed to be the main factors contributing to this. This paper aims to discuss the aforementioned issue.

To explore the phenomenon empirically, the current study uses the survey data of 1,056 consumers from China and analyses them using ordered logistic regression.

The results revealed that consumers' cognitive bias significantly affects their behaviour toward broiler products, and the order of influence is cognitive bias regarding industry cognitive > product nutrition and taste > food safety. The study further revealed that the more diverse the information acquisition channels, the more likely they are to promote consumer behaviour toward broiler chickens. The order of influence of the channels was self-organising > new media > traditional media.

Overall, the findings suggest that the government and enterprises should strengthen and upgrade information channels to boost both the broiler industry and consumer consumption behaviour regarding poultry products.

Rather than the usual focus on the impact of consumer cognition on consumer behaviour, this study examines the impact of cognitive bias on consumer behaviour. Further, centring on broiler products with high protein, low fat and feed-to-meat ratios, this study explores the reasons the per capita consumption of broiler products in China is far lower than the national average.

This work aims to explore why people review their experienced online shopping in such a manner (promptness), and what is the potential relationship between the users’ review promptness and review motivation as well as reviewed contents.

To evaluate the customers’ responses regarding their shopping experiences, in this paper, the “purchase-review” promptness is studied to explore the temporal characteristics of users’ reviewing behavior online. Then, an aspect mining method was introduced for assessment of review text. Finally, a theoretical model is proposed to analyze how the customers’ reviews were formed.

First, the length of time elapsed between purchase and review was found to follow a power-law distribution, which characterizes an important number of human behaviors. Within online review behaviors, this meant that a high frequency population of reviewers tended to publish relatively quick reviews online. This showed that the customers’ reviewing behaviors on e-commerce websites may have been affected by extrinsic motivations, intrinsic motivations or both. Second, the proposed review-to-feature mapping technique is a feasible method for exploring reviewers’ opinions in both massive and sparse reviews. Finally, the customers’ reviewing behaviors were found to be mostly consistent with reviewers’ motivations.

First, the authors propose that the “promptness” of users in posting online reviews is an important external manifestation of their motivation, product experience and service experience. Second, a semi-supervised method of review-to-aspect mapping is used to solve the data quality problem in mining information from massive text data, which vary in length, detail and quality. Finally, a huge amount of e-commerce customers’ purchase-review promptness are studied and the results indicate that not all product features are responsible for the “prompt” posting of users’ reviews, and that the platform’s strategy to encourage users to post reviews will not work in the long term.

Since its inception in 2009, the growth of real-time bidding (RTB) advertising has been dramatic. Yet, there is a dearth of research in the information system (IS) literature despite the potential for negative e-commerce outcomes. The purpose of this paper is to identify salient antecedents of users’ attitude toward RTB advertisements.

A research model was constructed and tested with data from 437 respondents. SmartPLS 3.0, a partial least square (PLS) structural equation modeling (SEM) tool, was used to evaluate the research model and test the hypotheses.

The findings indicate that user attitude is determined by opposing influences from the cognitive and affective attributes of an RTB advertisement. A surprise is found to elicit greater perception of advertisement personalization, timeliness and relevance, as well as privacy and intrusiveness concerns. While RTB advertisement relevance appears to lessen the effect of advertisement intrusiveness, privacy concern is exacerbated when the advertisement is more personalized. The authors discuss the implications of this study for click-through intentions and e-commerce.

At this point in the evolution of RTB advertising, the findings indicate that the surprise generated by the appearance of an RTB advertisement is not currently a “bad” surprise. In addition, the formation of positive user attitude toward RTB is complex because cognitive factors interact with users' concerns to strengthen or weaken the negative effects. The authors also demonstrate that attitude and stimulus–organism–response (S–O–R) theories are useful theoretical bases for the development of causal models to predict RTB attitude and click-through intentions.

Supplier–supplier coopetition is vital to buyer innovation in reality. However, it has not received enough attention in prior research. Integrating the ability-motivation-opportunity framework of organizational learning perspective and the awareness-motivation-capability framework of competitive dynamics theory, this paper investigates the effect of supplier–supplier coopetition within supplier network on buyer innovation, as well as the contingent role of the relational attributes -- duration and tie strength dispersion of buyer–suppliers relationship at the supplier network level.

Testing this model on the secondary data of supply networks formed by 204 US listed buyer firms in SIC code 28, 35, 36 during 2008–2019, the authors utilize a fixed-effect regression model to investigate the relationship between supplier–supplier coopetition and the focal buyer's innovation.

The authors provide support for the positive influence of supplier–supplier cooperation on buyer innovation and an inverted U-shaped relationship between supplier–supplier competition and the focal buyer's innovation. The buyer–suppliers tie strength dispersion amplified the above two effects, and supplier–supplier cooperation mitigates the effect of supplier–supplier competition on the focal buyer's innovation.

Extending the traditional dyadic view to a network-level view via linking the supplier–supplier dyad and the buyer–suppliers dyad, this paper contributes to a better understanding of supplier–supplier coopetition and its impact on buyer innovation with learning and competitive tension as the underlying explanations, and validates the contingent role of buyer–suppliers relational attributes.