Search results

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

From an agency perspective, the authors investigate whether family ownership and control configurations are systematically associated with a firm's choice of auditor and audit fees. Agency theory is an economic theory that purposes the existence of a contract between two parties, principals and agents. Auditor choice and audit fees by family firms provide interesting insights given the unique nature of the agency problems faced by such firms.

The authors employ Big-4 auditors (PWC, KPMG, E&Y and Deloitte) as a proxy for high quality auditor (Big N) for the auditor choice model. For the audit fee model, the dependent variable is the natural logarithm of audit fees (LnAF). The authors use two measures for family firm as explanatory variables: (1) a dummy variable (FAM_Control), which equals one if the firm is classified as a family firm and (2) FAM_Ownership, which is an indicator variable with a value of one if a firm has family members who hold CEO position, occupy board seats, or hold at least 10% of the firm's equity. Data of Chinese listed firms from 2011 to 2021 are used. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

The findings suggest that compared with non-family firms, Chinese family firms have a less tendency to employ Big-4 auditors due to less severe agency problems between owners and managers. Additionally, Chinese family firms sustain higher audit fees than non-family firms. Similar to the prior literature, however, Chinese family firms audited by Big-4 auditors incur lower audit fees than family firms audited by non-Big-4 auditors in this study. In contrast to young-family firms, old-family firms are less likely to pick top-tier auditors and sustain lower audit fees. Consistent and robust results are found from endogeneity tests and sensitivity analyses.

The empirical evidence provides a unique insight, for accounting practitioners, policymakers, family owners and other capital market participants concerning the diverse effects of various family ownership and control features on selecting high-quality auditors and audit fees. This study advances the understanding, showing that a lower demand for audit quality occurs in Chinese family firms as they encounter less severe Type I agency problems. However, the more severe Type II agency problems in Chinese family firms sustain higher audit fees due to higher audit risk and greater audit effort.

Whilst professional learning communities (PLCs) have been widely explored at the school level, they have received less attention at the departmental level. The study takes the variance between departments and the role of departmental teacher leaders into consideration, and the relationships amongst departmental-level PLC dimensions, two types of teacher leadership (TL) and individual teacher self-efficacy are investigated.

The sample consisted of 907 teachers from 81 departments in Chinese schools. The associations between the studied variables were explored through a multi-level analysis approach.

The results show that two specific characteristics of departmental PLCs, namely reflective dialogue (RD) and collective responsibility (CR), exhibit a positive correlation with individual teacher self-efficacy. Additionally, the findings indicate that teacher transformational leadership significantly predicts teacher self-efficacy, whereas teacher instructional leadership (IL) does not emerge as a significant predictor. These findings may be attributed to the contextual factors of Chinese teachers' collective work and the practice of teacher leaders.

This research contributes to the existing literature by addressing the variance between departments and uncovering the impacts of departmental PLC dimensions on individual teachers. Furthermore, two TL styles at the departmental level are differentiated, and their distinct influences on teacher self-efficacy are further analysed.

Session-based recommendation aims to predict the user's next preference based on the user's recent activities. Although most existing studies consider the global characteristics of items, they only learn the global characteristics of items based on a single connection relationship, which cannot fully capture the complex transformation relationship between items. We believe that multiple relationships between items in learning sessions can improve the performance of session recommendation tasks and the scalability of recommendation models. At the same time, high-quality global features of the item help to explore the potential common preferences of users.

This work proposes a session-based recommendation method with a multi-relation global context–enhanced network to capture this global transition relationship. Specifically, we construct a multi-relation global item graph based on a group of sessions, use a graded attention mechanism to learn different types of connection relations independently and obtain the global feature of the item according to the multi-relation weight.

We did related experiments on three benchmark datasets. The experimental results show that our proposed model is superior to the existing state-of-the-art methods, which verifies the effectiveness of our model.

First, we construct a multi-relation global item graph to learn the complex transition relations of the global context of the item and effectively mine the potential association of items between different sessions. Second, our model effectively improves the scalability of the model by obtaining high-quality item global features and enables some previously unconsidered items to make it onto the candidate list.

This paper examines whether and how customers' annual report tone affects suppliers' innovation decisions.

Using the data from disclosed information on top five customers and annual report tone by Chinese listed firms, this paper used a two-way fixed effect model and intermediary effect model tests to explore the impact of customers' annual report tone on suppliers' innovation decisions.

The results indicate that the more positive the tone of customer annual reports is, the higher the suppliers' technological innovation level. The customers' annual report tone affects suppliers' innovation decisions through alleviating financing constraints and reducing the bullwhip effect. In addition, the authors find that the worse the supplier's bargaining power and the higher the customer's media coverage, the more significant the impact of positive customer annual report tone on the level of corporate technological innovation.

For downstream customers, to improve the quality of their text information disclosure. For upstream suppliers, the tone of customers' annual reports has incremental information, so the attention to customers' text information should be strengthened. As far as the market is concerned, it is recommended that regulators should strictly require the quality of text information disclosure and introduce relevant penalty mechanisms better to regulate the quality of corporate text information disclosure.

To the best of the author's knowledge, this paper is the first to expand the research related to textual information from a supply chain innovation perspective. The textual information can provide incremental information, and spillover effects may occur among supply chains, affecting suppliers' innovation decisions. And it clarifies the specific mechanism by which the supply chain tone spillover effect affects corporate innovation, enriching the relevant research on supply chain influence mechanisms.

The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the response surface optimization method. This study has extraordinary implications for the planning of future intelligent transportation.

First, the single vehicle and vehicle platoon models are validated. Second, the configuration with the lowest average drag coefficient under the two conditions is obtained by response surface optimization. At the same time, the aerodynamic characteristics of the mixed platoon driving under different conditions are also analyzed.

The configuration with the lowest average drag coefficient under no crosswind conditions is 0.3 L for longitudinal spacing and 0.8 W for lateral spacing, with an average drag coefficient of 0.1931. The configuration with the lowest average drag coefficient under crosswind conditions is 10° for yaw angle, 0.25 L for longitudinal spacing, and 0.8 W for lateral spacing, with an average drag coefficient of 0.2251. Compared to the single vehicle, the average drag coefficients for the two conditions are reduced by 25.1% and 41.3%, respectively.

This paper investigates the lowest average drag coefficient for mixed platoon driving under no crosswind and crosswind conditions using a response surface optimization method. The computational fluid dynamics (CFD) results of single vehicle and vehicle platoon are compared and verified with the experimental results to ensure the reliability of this study. The research results provide theoretical reference and guidance for the planning of intelligent transportation.

The purpose of this study is to propose a new method for the end-to-end classification of steel surface defects.

This study proposes an AM-AoN-SNN algorithm, which combines an attention mechanism (AM) with an All-optical Neuron-based spiking neural network (AoN-SNN). The AM enhances network learning and extracts defective features, while the AoN-SNN predicts both the labels of the defects and the final labels of the images. Compared to the conventional Leaky-Integrated and Fire SNN, the AoN-SNN has improved the activation of neurons.

The experimental findings on Northeast University (NEU)-CLS demonstrate that the proposed neural network detection approach outperforms other methods. Furthermore, the network’s effectiveness was tested, and the results indicate that the proposed method can achieve high detection accuracy and strong anti-interference capabilities while maintaining a basic structure.

This study introduces a novel approach to classifying steel surface defects using a combination of a shallow AoN-SNN and a hybrid AM with different network architectures. The proposed method is the first study of SNN networks applied to this task.

This study aims to reduce the construction safety accidents of prefabricated building (PB) projects, improve the efficiency and effectiveness of safety supervision by government departments, and provide theoretical reference for improving the safety supervision system of PB construction.

Considering the information asymmetry between government supervision departments and construction contractors and the interactive relationship between the two parties under bounded rationality, we propose an evolutionary game model for the construction safety dynamic supervision of PBs and analyze the evolutionary strategy of the game. The system dynamics (SD) method is used to simulate and analyze the evolutionary game process under a dynamic supervision strategy and the adjustment of external variables.

The cost difference between the government's strong and weak supervision, the construction contractor's additional expenditure for strengthening safety management, and other factors affect system stability. The government can dynamically adjust the penalties based on the construction contractor's subjective willingness to ignore safety management and further adjust their rate of change based on the completion of the supervision goals to improve the efficiency and effectiveness of construction safety supervision.

This study makes contributions in two areas. Through a combination of SD and an evolutionary game, it provides new insights into the strategic choice of the main body related to PB construction safety. Additionally, considering the nonlinear characteristics of construction safety supervision, it provides useful universal suggestions for PB construction safety.

With the continuous improvement of social and economic development as well as the rising level of demand for spiritual life, the design of cultural and creative products has ushered in new opportunities and challenges. Therefore the research related to cultural and creative products design is an inevitable choice for industrial innovation and market competition. The article aims to analyze the frontier hotspots and trend evolution of theoretical research on cultural and creative design in China by presenting different research fields, personnel and institutions embodied by cultural and creative products, thus providing a forward-looking development reference for China's special cultural and creative product design practice.

In this paper, the visualized citation analysis tool — CiteSpace V is used to analyze and map the relevant literature of Chinese cultural and creative design in CNKI (Chinese National Knowledge Infrastructure) as the data sources, through bibliometric methods, in order to study the application development of Chinese cultural and creative design and provide reference for the application research of Chinese cultural and creative industries.

With the improvement of China's comprehensive strength, cultural self-confidence and strategy are being paid more and more attention by scholars; with the future research of China's cultural and creative design theory, cross-integration becomes the future trend; with the gradual maturity of China's cultural and creative design methodology, how to choose the right method for pioneering research is a difficulty for the future development of cultural and creative design; with the continuous development of China's economy, the method construction of innovative cultural and creative industry system becomes the focus of future research; with the continuous progress of science and technology, the integration of emotion and product industry is the mainstream of future development on cultural and creative design.

Through an objective empirical analysis of the development of Chinese cultural and creative products, it will broaden the research horizons of relevant scholars, understand the development direction of China's cultural and creative industries, enrich the design practice application of Chinese cultural and creative products, enhance the understanding of international counterparts on Chinese cultural and creative design research and promote the exchange among international counterparts.

This paper examines the impact of state control on stock price crash risk given whether and how ownership structure affects stock price crash risk is relatively underexplored.

The sample includes 2,285 Chinese firms listed in the Shanghai and Shenzhen Stock Exchanges. Panel data is used for conducting the analysis and endogeneity is addressed with instrumental variable estimation and by testing how stock price crash risk is affected when the ultimate controller changes from a private-owned company to a state-owned enterprise.

The authors find that state control is negatively associated with future stock price crash risk. The mechanism analysis shows that state control reduces stock price crash risk through the implementation of conservative corporate policies. Furthermore, the impact of state control is more pronounced with more intensive state involvement, e.g. in strategic industries and when a company's ultimate controller is a non-corporate government agency or the central government.

This paper enriches the literature on the controversy of the role of state control and the results of this study highlight the importance of the conservatism of state control on reducing stock return tail risk. The authors also add to the literature on the importance of the policy-risk sharing effect of state ownership.