Search results

The purpose of this paper is to prove that the technology that customers accept is sometimes not the most advanced, but backward, and to explain why different technologies could coexist under certain market situations and government regulations.

A general model was developed to analyze choice of technology regime under evolution of market demand and government regulation led by evolutionary economics.

Market demands and government regulations can affect the change of technology regime deeply, regardless of the level of certain technology. With the change of environment factors which affect China's mobile phones technological evolution, this paper testifies to the rationality and inevitability of PHS's market success and indicates that government regulations would impact the technological choice and lead to some technology market success, but it would lead to low efficiency of resources allocation.

The paper provides an instrument for analyzing the co‐evolution of market demand, government regulation and technology regime.

The purpose of this paper is to analyze the coordination of Chinese technology policy and assess its contribution to technology progress and economy development.

A method was developed to assess the coordination and its tendency of technology policy based on technology policy quantification. In addition, econometric models were built to estimate performance of technology policy coordination.

Chinese technology policy coordination shows significant characteristics in different periods; the level of policy coordination is promoted rapidly because the institutional path‐dependence and the competition of benefits among departments have aggravated an already unbalanced emphasis on the wording of the technology policy during the process of economic and political reform. The coordination among departments, coordination of policy goals and coordination of policy means play different roles in technology progress and economy development.

Because of the limitation of data and time, the paper cannot assess the coordination among policy goals and policy means. Also, it is necessary to study the interaction of different principals and agencies during technology policy formulation and execution.

The methods in the paper can easily be used by decision makers evaluating the situation of technology policy coordination, and optimize policy based on the relationship of different policy targets and policy implements, especially the interaction of different principals and agencies.

The paper develops a method to assess technology policy coordination based on technology policy quantification and builds econometric models to assess its contribution to technology progress and economy development.

Sensor arrays and pattern recognition-based electronic nose (E-nose) is a typical detection and recognition instrument for indoor air quality (IAQ). The E-nose is able to monitor several pollutants in the air by mimicking the human olfactory system. Formaldehyde concentration prediction is one of the major functionalities of the E-nose, and three typical machine learning (ML) algorithms are most frequently used, including back propagation (BP) neural network, radial basis function (RBF) neural network and support vector regression (SVR).

This paper comparatively evaluates and analyzes those three ML algorithms under controllable environment, which is built on a marketable sensor arrays E-nose platform. Variable temperature (T), relative humidity (RH) and pollutant concentrations (C) conditions were measured during experiments to support the investigation.

Regression models have been built using the above-mentioned three typical algorithms, and in-depth analysis demonstrates that the model of the BP neural network results in a better prediction performance than others.

Finally, the empirical results prove that ML algorithms, combined with low-cost sensors, can make high-precision contaminant concentration detection indoor.

The purpose of this paper is to investigate the spillover effects of a bright-line disclosure regulation that required Chinese listed firms to provide earnings forecasts if they anticipated specified, large earnings changes.

The paper examines the discontinuity of the earnings change distribution of firms listed on the Shenzhen Stock Market between 2010 and 2014. The paper finds that firms no longer subject to the bright-line test still exhibited discontinuity in earnings change distribution. The discontinuity lasted for at least three years with magnitude comparable to that of the firms still subject to the bright-line test. In addition, newly listed firms that had never experienced the bright-line test showed similar tendency to avoid the same threshold. There is some evidence that these firms’ avoidance of the −50 per cent changes was partly because of market pressure.

Research on bright-line tests has to date focused on their immediate and direct effects on firms currently subject to such tests. This study finds that a bright-line disclosure regulation’s influence is not limited to the firms directly governed by the regulation. It could lead to widespread and long lasting distortions in financial reporting behaviors of firms not currently subject to such tests.

The paper has implications for regulators who study the economic consequences of bright-line regulations in general and analysts of the Chinese capital market in particular.

This is the first empirical report that bright-line disclosure regulations affected the financial reporting behavior of firms that were not directly subject to the bright-line tests.

This paper aims to discuss flow pattern transition (FPT) as an important factor in multiple-phase flow measurements. Several methods have been proposed to control FPT, but those methods fail to address the many issues in complex flow conditions that can affect flow patterns.

In this paper, a non-intrusive sensor instrumentation is applied to extract measurable data under different flow conditions. Using these data, a simple theoretical–mathematical method along with an orthogonal design is applied to FPT optimization. Orthogonal experiments are designed and carried out according to theoretical guidelines. Three selected process parameters – phase fraction, gas pressure in the initial independent process and liquid speed – are optimized for FPT results to produce a minimum FPT time.

The following results are obtained: the phase fraction in the initial independent process can lead to significant reductions in FPT time, gas pressure plays an important role and liquid speed has no apparent effect on FPT results. Under optimized conditions, FPT time can be shortened to 0.3-0.6 times by controlling the above three parameters compared with normal conditions.

The proposed method is simple, rapid and efficient for evaluating an FPT process and lays the foundation for further FPT applications.

This study aims to examine whether and how corporate sustainability capability influences energy efficiency through competitive intensity and slack resource availability.

The authors applied a two-wave research design and administered a survey questionnaire to senior-level managers of 78 ISO-14001 and ISO-50001 certified manufacturing companies. The authors use a multi-method approach for data analysis. AMOS 23 software was applied for covariance-based structural equation modeling. In addition, SPSS 25 software was applied for hierarchical regression analysis to examine the causal relationships in the model.

The finding reveals that corporate sustainability capabilities, which include energy-saving opportunities, seizing energy-saving opportunities and resource reconfiguration, significantly improve firms’ energy efficiency. In addition, competitive intensity and slack resource availability positively moderated the relationship between corporate sustainability capability and energy efficiency.

To the best of the authors’ knowledge, this study is the first to examine the link between corporate sustainability capability and energy efficiency in developing countries such as Pakistan. Although the influence of various corporate sustainability capabilities on sustainable performance has been widely examined in the literature, the role of corporate sustainability capability has been limitedly explored with energy efficiency. This study extends the literature by adding to the knowledge of corporate sustainability capability that enhances boundary conditions in developing countries.

For many optimization problems such as optimal techniques, compositions, producing process, the optimizing objectives in systems are complex relations with respect to a great deal of parameters. Generally, the objective function is hardly obtained, even the searching objective is unquantifiable. So it is difficult to model and optimize the complex systems to some extent.

To the above purpose, a novel approach is presented in this paper. It firstly utilizes the excellent fitting performance of neural network (NN) combined with expert knowledge (EK) to obtain the objective function, and secondly searches the optimal influential parameters with genetic algorithm (GA).

Peaks function inside Matlab and the acural application of comprehensive performance optimization in analog PID control system are studied, respectively. The results of simulation and the actual experiment both show that the modeling and optimizing method presented in the paper are effective.

Expert knowledge is needed for the fuzzy/unquantifiable objective.

The paper presents a useful way to model and optimize complex systems.

The combined approach based on NN, EK and GA is firstly presented and is effectively used in modeling and optimizing complex systems.

This study aims to review the current literature on the positive and negative effects of digitalisation in preventing corruption. It analyses existing research patterns and provides recommendations for future studies.

This paper employed bibliometric analysis and systematic review to scrutinise 190 papers from the Web of Science database from 2000 to 2023. Biblioshiny on R Studio was used for advanced bibliometric analysis to determine publication dynamics, influential journals, publications and impactful authors and a three-field plot to analyse relationships among countries, keywords and journals.

This study provides a bibliometric analysis of the past and actual developments in the field related to the effects of digitalisation on corruption. Based on the systematic literature review on a sample of the 50 most influential articles, this study identified background theories employed, the primary research methodologies adopted and valuable insights into both the positive and negative aspects of the impact of digitalisation on corruption.

This study provides an extended overview of the effects of digitalisation on corruption and advances new avenues for further research related to this field. The white and dark sides of the effects of digitalisation on corruption are highlighted. Furthermore, the study identifies the need for further research in this field to gain a more in-depth understanding of the nexus between digitalisation and corruption.