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Online knowledge integration has been an important concern of the online knowledge community as it can lead to various positive outcomes of online knowledge coproduction. This paper identifies online knowledge integration factors by considering group heterogeneity and group interaction process.

Based on the categorization-elaboration model (CEM) and interactive team cognition (ITC) theory, a research model that reflects the antecedent's factors and mediating factors of online knowledge integration was developed and empirically examined based on data collected from 2,339,836 data extracted from Wikipedia.

Group interaction process plays an essential mediator role in online knowledge integration. Group knowledge heterogeneity negatively influences online knowledge integration and group experience heterogeneity positively, and they both positively promote online knowledge integration through group interaction process with different paths.

Our research concerns the OKC context in one setting (Wikipedia). We expect that the results will generalize to other OKC platforms.

The findings of the study could assist the online knowledge community's organizers to understand the motivational mechanisms of online knowledge integration. Group interaction process could be regarded as the key role to promote group wisdom and maintain group independence.

We advance the understanding of the online knowledge integration and gain a richer understanding of the importance of group interaction independence for online knowledge integration based on the agreement of group wisdom. It suggested keeping group interaction independence is an important aspect for highly online knowledge integration among heterogeneity groups.

This study extends CEM and ITC theory to the domain of knowledge integration context and finds the mechanism between group heterogeneity and online knowledge integration by introducing the group interaction process.

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

Motivated by concerns and the ongoing debate regarding auditors’ independence and impartiality, this paper aims to examine the impact of the financial crisis on non-audit services (NAS) provision and audit quality (main and robust variables) in the four largest Eurozone countries together during the global financial crisis (GFC).

The authors used a time trend OLS model with a dummy variable as well as a baseline model with a dummy and control variables accounting for multicollinearity, considering the characteristics of the GFC.

It documented a positive (negative) relationship between NAS provision (audit quality) and crisis in four Eurozone countries, Germany, France, Italy and Spain, in the context of a baseline approach, supporting the hypotheses that there are higher non-audit fees and a lower audit quality. Moreover, it is revealed that NAS provision and audit quality behave similarly, using a time trend approach, during the GFC. Considering the role of the auditor specialization or not (Big4 vs non-Big4) in companies, a significant effect from crisis on non-audit fees and audit quality for the four countries under the baseline approach is found. In general, the findings persist for NAS provision and audit quality using the robust methods of the time trend and panel OLS approaches. Multicollinearity was not found to affect the findings of the regressions.

The study provides important implications for firm managers, auditors and regulatory authorities.

To the best of the author’s knowledge, it is the first time that the impact of the crisis on non-audit fees and audit quality is investigated during the GFC with two sets of OLS models (a time trend OLS with a dummy and a panel OLS with a dummy and control variables) in four largest Eurozone countries together.

At present, one of the key equipment in pillar industries is a large rotating machinery. Conducting regular health monitoring is important for ensuring safe operation of the large rotating machinery. Because vibrations sensors play an important role in the workings of the rotating machinery, measuring its vibration signal is an important task in health monitoring. This paper aims to present these.

In this work, the contact vibration sensor and the non-contact vibration sensor have been discussed. These sensors consist of two types: the electric vibration sensor and the optical fiber vibration sensor. Their applications in the large rotating machinery for the purpose of health monitoring are summarized, and their advantages and disadvantages are also presented.

Compared with the electric vibration sensor, the optical fiber vibration sensor of large rotating machinery has unique advantages in health monitoring, such as provision of immunity against electromagnetic interference, requirement of less insulation and provision of long-distance signal transmission.

Both contact vibration sensor and non-contact vibration sensor have been discussed. Among them, the electric vibration sensor and the optical fiber vibration sensor are compared. Future research direction of the vibration sensors is presented.

Using the combined theoretical umbrella of organizational legitimacy theory, service-dominant logic, fairness heuristic theory and two-factor theory, the purpose of this paper is to investigate the effectiveness of different food recall strategies (recall proactiveness and compensation) in terms of both how consumers react (perceived organizational legitimacy and purchase intention) and how recall norms would influence the effectiveness in three countries. In addition to the reporting of important results, this paper provides implications for food companies to handle effectively the recalls, especially when the recalls are cross-country.

A 2 compensation (high vs low) ×2 recall strategy (proactive vs passive) scenario experiment was conducted in Hong Kong, the USA and Mainland China. After checking the effectiveness of manipulation, the paper tested the main effect and interaction effect of recall proactiveness and compensation on perceived organizational legitimacy and purchase intention. In addition, the mediating effect of perceived organizational legitimacy between recall strategies and purchase intention was also tested.

Significant main effect, interaction and mediation effect were found across the three countries with a different pattern. For the USA and Mainland China which have strong recall norms, the interaction found followed the predictions of the two-factory theory. However, the pattern found in Hong Kong, which has weak recall norms, followed the predictions of the fairness heuristic theory. Full mediation effect of perceived organizational legitimacy between compensation and purchase intention was found in the USA and Mainland China, while it was only partial in Hong Kong. For the mediation between proactiveness and purchase intention, full mediation was found in Hong Kong and the USA, while it was only partial in Mainland China.

First, this study differentiated food recall strategy into two dimensions – recall proactiveness and compensation. Second, this study tested the applicability of two-factor theory and fairness heuristic theory in recalls by testing the competing hypotheses proposed according to the two theories. Finally, this study can further help our understanding of the recall effectiveness across different recall norms.

To examine whether and how the different levels of regional economic incentives would have an effect on underwriters' market share in general.

Drawing on Chinese IPO firms during the period 2006-2016, this study examines the impact of different levels of regional economic incentives on underwriters' market share.

The authors find that regional economic incentives have a positive impact on underwriters' market share and that local economic incentives have a significantly stronger impact than central economic incentives. Furthermore, the authors find that IPO firms with underwriters driven by regional economic incentives experience worse post-IPO performance than firms with underwriters driven by central economic incentives, which do not experience a significant decline in post-IPO performance.

Taken together, the authors’ findings are consistent with the notion that performance assessment motivates officials at various levels of government to bring companies in their jurisdiction to the IPO market prematurely. In addition, the results indicate that central economic incentives play a significant role in driving China's macroeconomic development and market-oriented system reforms. As such, they are one of the major driving forces behind China's market-oriented system reforms.

The purpose of this study is to provide further evidence on the ongoing debate on the costs and benefits of mandatory audit partner rotation (MPR). Specifically, this study examines how MPR simultaneously affects audit reporting lag (ARL) and audit fees (AFs).

A simultaneous approach was adopted to further shed light on the findings currently documented by this line of research.

Using Australian data, it was found that MPRs increase AFs but do not affect ARL simultaneously in the year of MPRs. It was also found that the departing audit partners do not charge higher fees or delay the completion of the audits in the final year before their departure and that neither AFs nor ARL changes significantly for the second round of MPRs.

To the best of the authors’ knowledge, no prior study on MPR has examined the issue using a simultaneous approach although failure to consider the simultaneous effect of interrelated variables may lead to estimation biases and problems of parameter identification. The results herein provide further evidence that the clients do not bear both costs of paying higher AFs and having the delayed audits and that the costs associated with MPRs do not occur earlier and the costs associated with MPRs may dissipate over time.

As humans are influenced by their environment, this study explores how different construal levels of ambient scent temperature affect consumers’ food choices.

This study employed a series of experimental methods from three studies, totalling five experiments. The experiments involved both laboratory and field settings, as well as neuroscientific techniques, thus generating empirical evidence.

Three studies were conducted to investigate how construal levels of both ambient scent temperature and tasks influenced food choice. Study 1 found that the construal level of ambient scent temperature significantly affected the type of food consumed. Study 2 included the task’s construal level as another factor to examine whether it interacted with the ambient scent temperature construal level. Both factors were significant, but only when perceived by the participants simultaneously. If the task’s construal level was manipulated before exposure to the ambient scent temperature, the latter did not have a significant effect. Study 3 employed a neuroscientific method to explore the mechanism behind the match between ambient scent temperature and food choices based on construal levels. The congruence of ambient scent temperature and food choice based on construal level enhanced positive emotions.

The sample size, although in line with other neuroscientific studies, was not sufficiently large for robust generalizability. This limitation can encourage future research to increase the number of participants and thus enhance the accountability of the findings. Another limitation is the participants’ cultural background.

This study’s practical implications are twofold. First, odour intensity was perceived to be the strongest in hot samples (Kähkönen et al., 1995), and we confirmed how ambient scent temperature can influence one’s food choice. Thus, food business operators can use warm ambient scent temperatures to promote hedonic food or snacks. Second, participants’ positive emotions were enhanced by the congruence of ambient scent temperature and food choice.

The association between ambient scent temperature and food choice has been extensively researched. However, this study provides an empirical explanation for the application of CLT. Accordingly, we performed a series of laboratory and field experiments using behavioural and neuroscientific approaches. The results confirmed that the construal level of ambient scent temperature significantly affected food choice. Moreover, the FAA revealed that one’s positive emotions would be prompted if there was congruence in the construal levels of ambient scent temperature and food choice.

This study has theoretical and managerial value because people’s poor understanding of food selection is affected by ambient scent temperature. Moreover, its novelty lies in the application of a neuroscientific approach to one experiment.

Internet technology allows millions of people to find high quality medical resources online, with the result that personal healthcare and medical services have become one of the fastest growing markets in China. Data relating to healthcare search behavior may provide insights that could lead to better provision of healthcare services. However, discrepancies often arise between terminologies derived from professional medical domain knowledge and the more colloquial terms that users adopt when searching for information about ailments. This can make it difficult to match healthcare queries with doctors’ keywords in online medical searches. The paper aims to discuss these issues.

To help address this problem, the authors propose a transfer learning using latent factor graph (TLLFG), which can learn the descriptions of ailments used in internet searches and match them to the most appropriate formal medical keywords.

Experiments show that the TLLFG outperforms competing algorithms in incorporating both medical domain knowledge and patient-doctor Q&A data from online services into a unified latent layer capable of bridging the gap between lay enquiries and professionally expressed information sources, and make more accurate analysis of online users’ symptom descriptions. The authors conclude with a brief discussion of some of the ways in which the model may support online applications and connect offline medical services.

The authors used an online medical searching application to verify the proposed model. The model can bridge users’ long-tailed description with doctors’ formal medical keywords. Online experiments show that TLLFG can significantly improve the searching experience of both users and medical service providers compared with traditional machine learning methods. The research provides a helpful example of the use of domain knowledge to optimize searching or recommendation experiences.

The authors use transfer learning to map online users’ long-tail queries onto medical domain knowledge, significantly improving the relevance of queries and keywords in a search system reliant on sponsored links.

The technical level of aircraft failure analysis plays a special role in ensuring the safety of civil aviation flight. Using appropriate methods for functional failures analysis can provide a reliable reference for aircraft safety. The purpose of this paper is to provide a new and comprehensive measure based on conventional functional hazard analysis (FHA) and grey system theory to analysis and evaluate the class that each failure belongs to.

This paper integrates multiple methods including the FHA, the fixed weight cluster, the Delphi method and the analytic hierarchy process (AHP). To begin with, use FHA method to sort out the corresponding failure states of a certain system from the perspective of function and determine the evaluation index. And then using group decision and AHP, determine the expert weight and index weight in the fixed weight cluster. The fixed weight cluster function is used to determine the grey class to which a certain functional failure belongs in the complex system.

In the past, the risk assessment of aircraft was mostly dominated by the subjective judgment of the experts, but it was not possible to give an objective observation score for each failure state. This paper addresses the problem efficiently as well as the feature of “little data, poor information.” The risk degree of each failure state can ultimately be replaced by a quantitative value.

This paper uses the idea of clustering in grey system theory to evaluate the risk of landing gear system. In the expert evaluation stage, different experts evaluated the impact degree of the aircraft's failure caused by its functions, so the final risk classification is subjective to some extent.

This study analyzed the different conditions of the landing gear, including the front wheel steering, front wheel damping, front wheel steering system, brake system fault information and so on. It can effectively divide the different failure states and their effects, which is helpful to improve the safety of aircraft landing gear system and provide some useful methods and ideas for studying the safety of aircraft systems.

Based on the FHA analysis process and the grey system theory, this paper determines various potential risks and their consequences of various functions according to the hierarchy, so as to carry out further detailed analysis on the risks that may occur under various functional conditions and take certain measures to prevent them. It is helpful to improve the risk management and control ability of aircraft in the actual flight process and to guarantee the safety of people's lives and property.

This paper is a pioneer in integrating the FHA method and the grey system theory, which exactly can be used to address the problem with the character of “little data, poor information.” The model established in this paper for the defects of FHA can effectively improve the accuracy of FHA, which is of great significance for the study of safety. In this paper, a case about landing gear system is given to illustrate the effectiveness of the model.