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Internal knowledge transfer is crucial for firms to improve their employees’ abilities and improve their work performance. However, there is still a gap in the knowledge management field regarding whether internal knowledge transfer can leverage employee personality traits and service performance in service-oriented organizations. To address this gap, this study aims to validate a multilevel model of the mediating (i.e. internal knowledge transfer as a mediator) and moderating (i.e. task interdependence as a moderator) mechanisms underlying personality traits and employee service performance.

Multilevel structural equation modeling was applied for model validation using an original data set from 45 team leaders and 333 employees working in Chinese hotels.

Internal knowledge transfer mediated the link between extraversion and employee service performance and the link between openness to experience and employee service performance. Task interdependence played a moderating role that strengthened both the impacts of extraversion and openness to experience on internal knowledge transfer.

Through the use of an original data set, this study advances the knowledge management discipline by investigating the mediating impact of internal knowledge transfer between personality traits and employee service performance and revealing the moderating impact of task interdependence that underlies the links between personality traits and internal knowledge transfer.

Innovation for service contributes to service quality and customer satisfaction, and further benefits service-centered organizations to sustain competitive advantages. However, concurrent mediating and moderating mechanisms underlying innovation for service at both the group and individual levels have been scarcely investigated. The purpose of this study is to explore multilevel mediating and moderating mechanisms behind the relationship between dual-level transformational leadership (TFL) and innovation for service at the group and individual levels.

Data were collected from two countries (i.e. China and Australia). Multilevel structural equation modeling was employed to validate the research model. Bootstrapping with 5,000 replications and latent moderated structural equation modeling were used to respectively examine the mediating and moderating mechanisms.

The cross-national results showed that task interdependence and creative role identity respectively played as the group-level and individual-level mediating roles between TFL and innovation for service. It was also found that task interdependence played as a cross-level predictor enhancing individual innovation for service. Task interdependence was a moderator on the relationship between individual-level TFL and creative role identity among Australian employees, but not among Chinese employees. The relationship between creative role identity and individual innovation for service was not moderated by task interdependence among both Chinese and Australian employees.

This study contributes to advancing the TFL–innovation research through revealing dual-level TFL as the antecedent of innovation for service at both the group and individual levels. It also extends the understandings of the mediating and moderating mechanisms behind this dual-level relationship between TFL and innovation for service.

Service innovation benefits hospitality organizations’ service quality and competitive advantages. However, how and when team culture amplifies team service innovation is still not fully comprehended. Thus, this study aims to reveal the mediation and moderation mechanisms behind the team-level culture and service innovation nexus.

This study used both quantitative and qualitative methods to validate the research model. The authors collected data from leaders and their members working in the hospitality sector in China.

The results demonstrated the positive nexus of developmental culture and team service innovation. This nexus was sequentially mediated by aggregated creative role identity and aggregated creative self-efficacy and was also strengthened by task interdependence.

The results indicated that hospitality practitioners should consistently instill the values of developmental culture into their members to trigger their teams’ service innovative endeavors. They should also design more tasks requiring intensive teamwork and encourage members to complete these tasks collaboratively.

This study advances the understanding of the direct, mediating and moderating effects behind team service innovation.

Service innovative behavior from employees helps hospitality organizations gain a competitive advantage and sustain business flourishment. Although group diversity has been demonstrated as a predictor of employee outcomes, whether group diversity in terms of extraversion and openness enhances employee service innovative behavior remains a gap. This study aims to fill this gap by developing a multilevel model of the direct relationship between group diversity in terms of extraversion and openness and employee service innovative behavior and also the mediations and moderations behind the relationship.

The authors collectd data from 44 Chinese hospitality teams. The research model was validated by multilevel structural equation modeling.

Results showed that both group extraversion diversity and group openness diversity fostered employee service innovative behavior via creative self-efficacy. Developmental culture strengthened the effectiveness of group openness diversity on creative self-efficacy and the effectiveness of creative self-efficacy on employee service innovative behavior. Nevertheless, developmental culture did not strengthen the effectiveness of group extraversion diversity on creative self-efficacy.

Findings suggest that managers and team leaders from hospitality organizations can elicit employee service innovative behavior through increasing group diversity in terms of extraversion and openness. Hospitality practitioners also should understand that employees’ confidence for creativity is able to channel group diversity into employee service innovative endeavors. Moreover, building developmental culture is essential for hospitality teams to strengthen the effect of group diversity on innovating services.

This study expands the diversity-innovation research through unfolding both the mediations and the moderations behind the link between group diversity in terms of extraversion and openness and employee service innovative behavior.

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.

The mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.

The simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity.

The algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

The purpose of this paper is to generate quantitative managerial insights for the improvement of the energy-saving potential and the coordinated development between economic growth and environmental protection.

A novel data envelopment analysis (DEA) model, based on the classical DEA theory, is developed from the perspective of emission reduction.

The empirical results indicate that China’s overall environmental efficiency is low and that there is huge improvement space for energy saving. Under the concerns of emission reduction, the energy-saving potential of the central region exceeds that of both the eastern and western regions. With regard to water, electricity and gas consumption, the electricity-saving potential exceeds the potential for both water saving and gas saving.

Previous studies rarely focused on the energy-saving potential, while considering environmental pollution. This paper applies a novel DEA method to evaluate the energy-saving potential of 30 Chinese provinces for 2015 with a focus on emission reduction concerns. Furthermore, both regional differences and energy type differences of the saving potential were analyzed.

This paper aims to investigate the effect and mechanism of O atom single doping, Ce and O atoms co-doping on the interfacial microscopic behavior of brazed Ni-Cr/diamond.

Using first-principles calculations, the embedding energy, work of separation, interfacial energy and electronic structures of Ni-Cr-O/diamond and Ni-Cr-O-Ce/diamond interface models were calculated. Then, the effect of Ce and O co-doping was experimentally verified through brazed diamond with CeO₂-added Ni-Cr filler alloy.

The results show that O single-doping reduces the interfacial bonding strength between Ni-Cr filler alloy and diamond but enhances its interfacial stability to some extent. However, the Ce and O co-doping simultaneously enhances the interfacial bonding strength and stability between Ni-Cr filler alloy and diamond. The in-situ formed Ce-O oxide at interface impedes the direct contact between diamond and Ni-Cr filler alloy, which weakens the catalytic effect of Ni element on diamond graphitization. It is experimentally found that the fine rod-shaped Cr₃C₂ and Cr₇C₃ carbides are generated on diamond surface brazed with CeO₂-added Ni-Cr filler alloy. After grinding, the brazed diamond grits, brazed with CeO₂-added Ni-Cr filler alloy, present few fracture and the percentage of intact diamond reaches 67.8%. Compared to pure Ni-Cr filler alloy, the brazed diamond with CeO₂-added Ni-Cr filler alloy exhibit the better wear resistance and the slighter thermal damage.

Using first-principles calculations, the effect of Ce and O atoms co-doping on the brazed diamond with Ni-Cr filler alloy is investigated, and the calculation results are verified experimentally. Through the first-principles calculations, the interface behavior and reaction mechanism between diamond and filler alloy can be well disclosed, and the composition of filler alloy can be optimized, which will be beneficial for synergistically realizing the enhanced interface bonding and reduced thermal damage of brazed diamond.

A good decision support system for credit scoring enables telecom operators to measure the subscribers' creditworthiness in a fine-grained manner. This paper aims to propose a robust credit scoring system by leveraging latent information embedded in the telecom subscriber relation network based on multi-source data sources, including telecom inner data, online app usage, and offline consumption footprint.

Rooting from network science, the relation network model and singular value decomposition are integrated to infer different subscriber subgroups. Employing the results of network inference, the paper proposed a network-aware credit scoring system to predict the continuous credit scores by implementing several state-of-art techniques, i.e. multivariate linear regression, random forest regression, support vector regression, multilayer perceptron, and a deep learning algorithm. The authors use a data set consisting of 926 users of a Chinese major telecom operator within one month of 2018 to verify the proposed approach.

The distribution of telecom subscriber relation network follows a power-law function instead of the Gaussian function previously thought. This network-aware inference divides the subscriber population into a connected subgroup and a discrete subgroup. Besides, the findings demonstrate that the network-aware decision support system achieves better and more accurate prediction performance. In particular, the results show that our approach considering stochastic equivalence reveals that the forecasting error of the connected-subgroup model is significantly reduced by 7.89–25.64% as compared to the benchmark. Deep learning performs the best which might indicate that a non-linear relationship exists between telecom subscribers' credit scores and their multi-channel behaviours.

This paper contributes to the existing literature on business intelligence analytics and continuous credit scoring by incorporating latent information of the relation network and external information from multi-source data (e.g. online app usage and offline consumption footprint). Also, the authors have proposed a power-law distribution-based network-aware decision support system to reinforce the prediction performance of individual telecom subscribers' credit scoring for the telecom marketing domain.

Banking is the key industry to guarantee the core leading role of finance in the process of economic development. It is important to study the bank efficiency and optimal allocation of bank’s resources. The purpose of our paper is to study the optimal allocation of resources between the bank savings system and loan system under the premise of environmental heterogeneity.

We use a two-stage meta-frontier Data Envelopment Analysis model to solve the relative efficiency of each city branch and use the multivariate statistical tools to analyze the empirical results.

This paper measures the relative efficiency of 16 Bank Branches of a state-owned bank in Anhui province considering regional heterogeneity. Based on the optimal resource allocation, we get the two-stage operation performance of all banks under group-frontier and meta-frontier and analyze the impact of the technical differences between the branches.

This study has a positive guiding significance for the banking industry to improve its operational efficiency in various business practices in the new era of big data. It will also provide practical suggestions and support for the government and relevant departments in the process of formulating macro-policies to ensure the healthy and stable development of the banking industry.