Search results

The accurate valuation of second-hand vessels has become a prominent subject of interest among investors, necessitating regular impairment tests. Previous literature has predominantly concentrated on inferring a vessel's price through parameter estimation but has overlooked the prediction accuracy. With the increasing adoption of machine learning for pricing physical assets, this paper aims to quantify potential factors in a non-parametric manner. Furthermore, it seeks to evaluate whether the devised method can serve as an efficient means of valuation.

This paper proposes a stacking ensemble approach with add-on feedforward neural networks, taking four tree-driven models as base learners. The proposed method is applied to a training dataset collected from public sources. Then, the performance is assessed on the test dataset and compared with a benchmark model, commonly used in previous studies.

The results on the test dataset indicate that the designed method not only outperforms base learners under statistical metrics but also surpasses the benchmark GAM in terms of accuracy. Notably, 73% of the testing points fall within the less-than-10% error range. The designed method can leverage the predictive power of base learners by incrementally adding a small amount of target value through residuals and harnessing feature engineering capability from neural networks.

This paper marks the pioneering use of the stacking ensemble in vessel pricing within the literature. The impressive performance positions it as an efficient desktop valuation tool for market users.

As the excessive lifting force can lead to catwalk rollover and well site accidents, the lifting process boundary conditions and structural parameters have a significant effect lifting force, it is important to analysis the structural parameters on the maximum lifting force in the lifting process of power catwalk.

A new model is proposed to analyze the influence of structure parameters on its lifting force for lifting power catwalk in this paper, and the geometric and dynamic equations are established according to the different boundary conditions in different stages. In addition, the establishment of dynamics equations is based on D'Alembert's principle. To solve the model, dynamic analysis software is developed, which uses c # call MATLAB to solve the geometric and dynamic equations. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

The best value of offset e is 0. The length of L22 should as small as possible while the installation size of the end of the conveying arm are guaranteed. The length of L1 should as small as possible while ensuring the not exceed the maximum value. The maximum lifting force remain the same in the second phase, the maximum lifting force decreases with the increase of Lcp, Lcpshould as small as possible. The maximum pressure of the hydraulic oil dropped by an average of 13.62% under optimized parameters.

This paper provides a theoretical basis for the selection of hydraulic winch, which also provides the theoretical basis and data support for the design and optimization of the structural parameters of the power catwalk.

This research has industrial applications in SJ Petroleum Machinery CO.LTD, SINOPEC (China) .CANRIG, North Rig, TESCO, Sichuan HONGHUA petroleum equipment CO.LTD of CNPC., Baoji Oil field Machinery CO.LTD, SJ Petroleum Machinery Co. LTD of SINOPEC, Yantai Jereh Oilfield Services Group CO.LTD, Nanyang clips oil equipment (group) CO. LTD, etc are the likely users.

A new model is proposed to analyze the lifting force of lifting power catwalk. The model takes into account the inertia force of the structure, development of dynamics software and analysis and optimization of structural parameters. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

In a people-oriented society, it is necessary to understand the electronic word of mouth (eWOM) of information service of the government. Government affair microblogs (GAM), which play an important role in orienting online opinions, listening to public voices, establishing government image, is an ideal channel to achieve this goal. In essence, the application of GAM is to improve the communication efficiency between the government and the public. The purpose of this study is to the influence factors of GAM eWOM which will not only benefits the government in better understanding the information dissemination rules of microblogs but also provides directions for the government to improve the information service over microblogs.

In this paper, the authors investigate and verify the regulating function, herd effect applied on GAM. The authors conduct an innovative empirical study based on perceived value theory, aiming to explore the factors that influence the eWOM of the Chinese Government.

Experiments on 502 GAM users show that social identification positively affects perceived value while effort cost negatively affects perceived value, and perceived value positively influences the microblogs’ eWOM. The authors also find that the herd effect positively regulates the relationship between perceived value and GAM’s eWOM. Theoretical and practical implications of these findings are discussed.

In this research, the regulating effect of herd effect on the relationship between perceived value and GAM’s eWOM has been explored. This study also provides inspirations for future government information service research and administrative measurement.

The impact of COVID-19 has led to a surge in the public’s reliance on the Internet for pandemic information, and the policy of home isolation has exacerbated this. This study aimed to investigate public information needs and ways of accessing and disseminating information during COVID-19 in mainland China.

This study used a qualitative research approach to conduct semi-structured interviews with 15 participants from 9 cities in mainland China about information needs and access behaviors during the COVID-19 outbreak. All interview recordings were converted into text and proofread, then coded and summarised in correspondence with the research questions using the grounded theory.

This study summarized the dynamics of public information needs during the 2.5-year pandemic and identified the difficulties in accessing certain information.

Although information needs of public health emergencies have been a hot topic during COVID-19, scant studies focus on information needs in specific countries in Asia, especially in mainland China, the first country with a major outbreak and stringent lockdown mandates. Therefore, the current study is well enriched by focusing on information demand behavior in the context of COVID-19. Possible measures for improvement were also given to existing and potential problems, taking into account the participants’ views.

The purpose of this study is to review the research about organizational career management (OCM) and provide an integrated understanding of OCM research.

In this paper, the authors systematically review 85 OCM-related papers published in highly influential journals over the past four decades (1978–2021). This paper reviews the definitions, measurements, antecedents, outcomes, mediators and moderators of OCM.

Diverse definitions of OCM exist, with three key common factors: what should be included in OCM, who is responsible for OCM and the goal of OCM. Scholars use different OCM measures, which might be due to different nations, industries, groups and scale development methods. More than 20 papers demonstrated the positive influences of OCM, providing convincing evidence of the necessity of OCM. About 90% of the current papers we reviewed (27 out of 30 papers) dominantly examined the influence of OCM on individuals’ attitudes or work behavior. The influence of OCM on organizational outcomes was less addressed.

First, the authors review the existing OCM measurements and distinguish two ways of measuring OCM: OCMP (organizational level, rated by HR managers or HR vice president or CEO, capturing the real practices) and POCM (Perceived OCM, individual level, rated by employees, capturing subjective perception of practices). This distinction reduces the ambiguity in existing measurements. Second, we summarize the empirical findings of OCM, including the antecedents, outcomes, mediators and moderators. These findings uncover the benefits/risks of OCM and the factors that may influence its effectiveness. Third, the review provides several practical implications as the findings can help managers improve their career development programs.

This study aims to examine the effects of payment methods used in mergers and acquisitions (M&A) conducted by UK companies spanning the period from 2007 to 2019.

The study used the estimated expected returns method to identify abnormal returns during the deal announcement period, applying event study analysis with both univariate and multivariate regression models to detect cumulative abnormal returns around the announcement timeframe.

The results show a short-term positive return increase for acquiring firms, controlling for deal-specific characteristics like target firm location and payment methods. The authors observed a preference for cash financing across domestic and cross-border transactions. Multivariate analysis revealed insignificance between payment methods and deal characteristics like cross-border acquisitions and diversification.

The study’s focus on publicly traded firms in the UK and the absence of a comparative analysis across different regions and markets limits the sample size and may impact the generalizability of findings.

The study proposes three practical implications. Firstly, firms should tailor payment methods to each transaction, aligning with strategic goals to optimize value and mitigate risks. Secondly, decision-makers must prioritize comprehensive due diligence and strategic alignment throughout M&A processes to enhance success and maximize synergies. Finally, analysing broader strategic contexts and regulatory landscapes when structuring transactions enables goal attainment, such as market expansion or value creation.

The study’s findings can promote transparency and accountability among corporate decision-makers in M&A transactions. Stakeholders can advocate for transparent decision-making processes, enhancing trust in corporate governance.

This study provides valuable insights into the impact of payment methods on shareholder value in M&A transactions involving UK companies, informing strategic decision-making and contributing to the understanding of corporate finance dynamics.

This study investigates whether and how place-based industrial relocation policy affects firm innovation.

By exploiting the establishment of China's National Industrial Relocation Demonstration Zones (NIRDZs) as a quasi-natural experiment in a difference-in-differences design, the authors examine the externalities of industrial policies that support sustainable development and growth from the perspectives of firms' patenting activities.

The study consistently finds that the NIRDZs policy significantly boosts local firm innovation, translating into a 60.46% increase in the patent applications of treated firms. The estimation results remain robust to a series of alternative specifications. Moreover, heterogeneity analysis suggests that the firms that benefited most were state-owned enterprises, firms with higher productivity, or firms in non-high-tech industries. Further, the authors find that the NIRDZs policy stimulates firm innovation mainly in the form of utility model patents, followed by designs and invention patents.

The results provide suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in policy implementation.

This study provides suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in the policy implementation.

This study fills the research gap by exploiting quasi-experiments to assess the effectiveness of state-led industrial policies for emerging economies. (2) The analysis sheds empirical light on how corporate innovation is motivated and financed by selective and functional industrial policies. (3) Theoretically, the results rationalize why state-led industrial relocation fuel innovation capabilities of localities from Marshall externalities and competition crowding-out effects.