Search results

The paper attempts to discuss the impact of reference price effect on pricing decisions.

With the growth of the Internet and e-commerce, more and more customers purchase products in through online channels and choose products by comparing different prices and services, and the reference price effect has an impact on pricing decisions. To investigate the impact of consumers' reference price effect on the dual-channel supply chain, the authors establish a basic model consisting of a single dominant manufacturer and a single downstream retailer, and analyze the optional decisions under different situations and discuss the influence of reference price effect. Finally, a number case verifies the validity and rationality of the proposed model.

The results show that (1) the reference price effect has varying effects on the price, channel demand and income of manufacturers and retailers in the channel depending on the role of customers' channel preferences. (2) The manufacturer's online channel demand and profits always increase with the reference pricing effect, whereas the retailer's offline demand and profits always decline. (3) When the proportion of consumers preferring offline is higher, the manufacturer's network price and wholesale price increase with the reference price effect, while the retailer's retail price decreases with the reference price effect; when the proportion of consumers preferring offline is lower, the opposite is true, and the centralized decision results are consistent with the decentralized decision results.

This paper can clarify the impact of consumer reference price effects on the operation of dual-channel supply chains, and help inform pricing decisions of manufacturers and retailers in dual-channel supply chains.

The proposed approach can well analyze the impact of consumer reference price effect and give channel their optional decisions.

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze, improve and control) and analyze the influencing factors of the mental health service system to study the implementation strategies of quality-oriented mental health services in middle schools.

This study was conducted in Tianjin, China, from September to November 2022, and 350 middle school students from Tianjin Public Middle School were selected as subjects. A questionnaire survey was used to collect data. In this study, the Six Sigma DMAIC method, sensitivity analysis method, exploratory factor analysis and principal component analysis were used to analyze the mental health services provided to middle school students.

Based on the Six Sigma DMAIC framework, this study indicates that the contribution rate of the mental health service process factor is the largest in the post-COVID-19 era. The mental health cultivation factor ranks second in terms of its contribution. Mental health quality and policy factors are also important in the construction of middle school students’ mental health service system. In addition, the study highlights the importance of parental involvement and social support in student mental health services during the post-COVID-19 era.

To the best of the authors’ knowledge, a study on middle school students’ mental health in the post-Covid-19 era has not yet been conducted. This study developed a quality-oriented mental health system and analyzed the influencing factors of mental health for middle school students based on data analysis and the Six Sigma DMAIC method.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation, the moderating role of entrepreneurial orientation and government institutional support between them.

Hierarchical regression analysis is adopted to test the hypotheses based on survey data provided by 223 manufacturing SMEs in China.

The results reveal that domestic and international collaboration networks positively affect SMEs' innovation performance. Business model innovation mediates domestic and international collaboration networks-SMEs’ innovation performance relationships. Entrepreneurial orientation positively moderates international collaboration networks–SMEs’ innovation performance relationship, and government institutional support positively moderates domestic and international collaboration networks–SMEs’ innovation performance relationships.

The findings indicate that managers of SMEs should invest in domestic and international collaboration networks and business model innovation to enhance SMEs' innovation performance. Moreover, entrepreneurial orientation and government institutional support should be valued when SMEs try to enhance their innovation performance by embedding in domestic and international collaboration networks.

This study broadens the authors' understanding of the relationship between collaboration networks and firms' innovation performance by classifying collaboration networks into domestic and international dimensions and investigating their direct impacts on SMEs' innovation performance. Besides, this study reveals how and when domestic and international collaboration networks influence the innovation performance of SMEs.

The elevator installation in old communities (EIOC) can effectively improve the public infrastructure of urban communities. However, differences in the decision-making behaviours of stakeholders lead to frequent conflicts, thereby hindering the implementation of EIOC. The purpose of this study is to explore the decision-making behavior of core stakeholders which are the government, community owners and elevator enterprises at different stages in the EIOC using the evolutionary game method.

A tripartite evolutionary game model involving the government, community owners and elevator enterprises was developed, and their evolutionary stabilisation strategies were explored in different stages. The dynamic change of the stakeholders' decision-making behaviours at different stages of the project and the influencing mechanism of the key factors on the decision-making behaviours of the three stakeholders were analysed through numerical simulation.

The results of this study showed that: Divergent interests led the government, community owners and elevator enterprises to adopt distinct decision-making behaviours at different stages, resulting in diverse attitudes and actions among stakeholders. A dynamic reward and penalty mechanism effectively motivated community owners and elevator enterprises to engage actively, fostering broad participation. However, the high regulatory cost diminished the government's regulatory effectiveness. This imbalance between penalties and incentives posed a challenge, impacting the overall effectiveness and efficiency of implementing the EIOC.

Existing research lacks exploration of the decision-making behaviours of stakeholders in community public infrastructure. This study developed a dynamic tripartite evolutionary game model in the EIOC from the gaming perspective. The results of this study provide a reference for dealing with the stakeholders' interests in the community public infrastructure and contribute to the theoretical basis for establishing an effective supervision mechanism.

The purpose of this paper is to prepare a multifunctional nanocomposite that is slow-release and resistant to seawater corrosion and biofouling corrosion and to explore the synergistic effect between the two corrosion inhibitors.

The morphology, structure and release properties of CAP@HNTs, BTA@HNTs and CAP/BTA@HNTs were investigated by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, specific surface area analysis and UV spectrophotometry. The corrosion resistance and antimicrobial properties were investigated by electrochemical measurements and bioinhibition rate tests, and the synergistic effect between the two corrosion inhibitors was explored by X-ray photoelectron spectroscopy.

The CAP/BTA@HNTs are responsive to acidic environments and have significantly improved antibacterial and corrosion resistance compared with CAP@HNTs and BTA@HNTs. CAP and BTA have a positive synergistic effect on anticorrosion and antifouling.

Two types of inhibitors, anticorrosion and antifouling, were loaded into the same nanocontainer to prepare a slow-releasable and multifunctional nanocomposite with higher resistance to seawater corrosion and biocorrosion and to explore the synergistic effect of CAP and BTA on corrosion resistance.

This paper introduces a novel method, Variance Rule-based Window Size Tracking (VR-WT), for deriving a sequence of estimation window sizes. This approach not only identifies structural change points but also ascertains the optimal size of the estimation window. VR-WT is designed to achieve accurate model estimation and is versatile enough to be applied across a range of models in various disciplines.

This paper proposes a new method named Variance Rule-based Window size Tracking (VR-WT), which derives a sequence of estimation window sizes. The concept of VR-WT is inspired by the Potential Scale Reduction Factor (PSRF), a tool used to evaluate the convergence and stationarity of MCMC.

Monte Carlo simulation study demonstrates that VR-WT accurately detects structural change points and select appropriate window sizes. The VR-WT is essential in applications where accurate estimation of model parameters and inference about their value, sign, and significance are critical. The VR-WT has also helped us understand shifts in parameter-based inference, ensuring stability across periods and highlighting how the timing and impact of market shocks vary across fields and datasets.

The first distinction of the VR-WT lies in its purpose and methodological differences. The VR-WT focuses on precise parameter estimation. By dynamically tracking window sizes, VR-WT selects flexible window sizes and enables the visualization of structural changes. The second distinction of VR-WT lies in its broad applicability and versatility. We conducted empirical applications across three fields of study: CAPM; interdependence analysis between global stock markets; and the study of time-dependent energy prices.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

As one of its major strategies, China has made a new plan to further expand High Standard Farmland (HSF) to all permanent basic farmland (80% of total farmland) for grain security over the next decade. Yet, what will be the impact of farmland infrastructure investment on agrifood systems? The paper aims to systematically evaluate the multiple effects (food security, economy, nutrition and environment) of expanding HSF construction under the context of the “Big Food vision” using an interdisciplinary model.

An interdisciplinary model – AgriFood Systems Model, which links the China CGE model to diet and carbon emission modules, is applied to assess the multiple effects of HSF construction on agrifood systems, such as food security and economic development, residents’ diet quality and carbon emissions. Several policy scenarios are designed to capture these effects of the past HSF investment based on counterfactual analysis and compare the effects of HSF future investment at the national level under the conditions of different land use policies – restricting to grain crops or allowing diversification (like vegetables, and fruit).

The investments in HSF offer a promising solution for addressing the challenges of food and nutrition security, economic development and environmental sustainability. Without HSF construction, grain production and self-sufficiency would decline significantly, while the agricultural and agrifood systems’ GDP would decrease. The future investment in the HSF construction will further increase both grain production and GDP, improve dietary quality and reduce carbon emissions. Compared with the policy of limiting HSF to planting grains, diversified planting can provide a more profitable economic return, improve dietary quality and reduce carbon emissions.

This study contributes to better informing the impact of land infrastructure expanding investment on the agrifood systems from multiple dimensions based on an interdisciplinary model. We suggest that the government consider applying diversified planting in the future HSF investment to meet nutritional and health demands, increase household income and reduce carbon emissions.

This research aims to examine how decision-makers’ demographic traits affect the integration of foreign workforce into Tirolean (Austria) companies. With continuous world migrations, Tirol experiences a great inflow of foreign workforce. While integrating into the workforce, the foreign workers interact with various decision-makers whose demographic traits (e.g., age, gender, nationality) potentially influence the success of the integration process. To gather data on the integration levels of a foreign workforce, the author conducted a questionnaire. Furthermore, several statistical analyses were run to determine if the relationship between demographic characteristics and integration success exists. The study reveals that demographic characteristics influence decision-makers’ acceptance of expatriates, as well as their recruitment, integration, and training and development outcomes. The empirical results indicate the strength of relationships identified through analyses. The study is limited to geographical, as well as the scope of the sample size, as the data are obtained from Tirol only. In addition, the results from the study serve as a basis for future discussions and research.