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This paper aims to examine the influence of information technology (IT) investment, including innovative IT investment and non-innovative IT investment, on comprehensive enterprise financial performance in a developing country, China.

This paper applies the method proposed by Barber and Lyon to construct the control group to study the impact of IT investment on financial performance of enterprises, using a sample of 229 IT investment announcement data of Chinese listed companies between 2011 and 2015.

The analysis of the financial benefits of these IT implementations yields mixed results. The results show that companies investing in IT can significantly improve profitability both the implementation and post-implementation periods for the full sample, improve the solvency only during the implementation phase, improve the growth ability after implementation time and cannot reduce business costs in all periods. At the same time, the authors find that, compared with non-innovative IT investment, the innovative samples do not achieve better financial performance, except the profitability financial indicator.

There are several limitations in this research. First, there is no large sample about the IT investment information data set in China, so this study was compelled to use limited sample data from China; hence, this could lead to errors of too early generalization. Second, the firms in the sample are all in China’s listed companies, so this may either not accurately or possibly could reflect the entire environment of developing countries.

First, it extends the scope of the established literature by examining the influence of IT investment with China’s public firms data and IT investment to see if such spending has had an influence on corporate financial performance. Second, there is a lack of research on the impact of IT investment on comprehensive financial performance of an enterprise, compared with the previous one-sided financial performance, such as profitability or financial cost. Third, as far as the authors are aware, there are no studies on the impact of IT investment on firm financial performance based on innovative and non-innovative classification.

The aim of this study is to determine the impact of different dimensions of consumer engagement in social media on firm performance in social media.

Beyond likes and comments, combined with the interactive behavior of consumer engagement with firms on social media, we proposed a set of metrics for consumer engagement on social media, namely personal engagement, user-interactive engagement, and fan-interactive engagement. We used the fixed-effect model and validated the impact of consumer engagement in different dimensions on firm performance.

The result shows that personal engagement and user-interactive engagement significantly correlate with firm performance; however, the same effect was not observed in fan-interactive engagement.

Prior researches on consumer engagement in social media are mainly about consumer engagement in firm-initiated social media page. In this study, we consider the consumer engagement behavior in firm-initiated and consumer-initiated social media pages, then validate the impact of different dimensions of consumer engagement on firm performance.

Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target.

The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo.

First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government.

The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts.

In the era of big data, there is doubt about the significance of causal inference as a paramount scientific task in the social sciences. Meanwhile, data-mining techniques rooted in big data and artificial intelligence (AI) have infiltrated numerous aspects of social science research. This study aims to expound the criticality of discerning causal relationships – beyond mere correlations – and scrutinizes the ramifications of big data and AI in the identification of causality.

This study discusses the challenges and opportunities for causality identification in the era of big data under the framework of potential outcomes model and structural causal model.

First, even in the age of big data, correlations that lack interpretability, robustness and feasibility cannot substitute causality. Second, the richness of the sample size does not help solve the problem of systematic bias in the process of causal inference. Furthermore, current AI research targets correlations rather than causality, thus creating difficulties in advancing from observations to counterfactuals.

This study provides insights into the impact of big data era on causal inference in the social sciences, with a view toward enhancing the pool of theoretical concepts available to researchers in relevant fields and accurately guiding the direction of scientific research in these fields.

The purpose of this paper is to describe and evaluate the time-varying and coupling dynamic characteristics of a 3-DOF parallel tool head.

From the view of control, a new dynamic index of a 3-DOF parallel tool head is proposed based on the dynamic model in the joint space. This index can reflect the time-varying and coupling dynamic characteristics which are the main characteristics of the parallel mechanisms, and its distribution in the whole workspace is also given. Through comparison of the dynamic load (driving current) of each driving shaft, a series of experiments is designed and carried out on a prototype to validate the effectiveness of the dynamic analysis. The tracking error of each driving shaft has also been taken into consideration.

The simulations of the index have the same variation law with the experimental results. The dynamic load of the driving shaft becomes larger with the increase of the dynamic index, and the dynamic performance becomes worse at the same time.

The main dynamic characteristics of the 3-DOF parallel tool head can be described and evaluated through this work.

The purpose of this study is to develop a modified parameter identification method and a novel measurement method to calibrate a 3 degrees-of-freedom (3-DOF) parallel tool head. This parallel tool head is a parallel mechanism module in a five-axes hybrid machine tool. The proposed parameter identification method is named as the Modified Singular Value Decomposition (MSVD) method. It aims to overcome the difficulty of choosing the algorithm parameter in the regularization identification method. The novel measurement method is named as the vector projection (VP) method which is developed to expand the measurement range of self-made measurement implements.

Newton Iterative Algorithm based on Least Square Method is analyzed by using the Singular Value Decomposition method. Based on the analysis result, the MSVD method is proposed. The VP method transforms the angle measurement into the displacement measurement by taking full advantage of the ability that the 3-DOF parallel tool head can move in the X – Y plane.

The kinematic calibration approach is verified by calibration simulations, a Rotation Tool Center Point accuracy test and an experiment of machining an “S”-shaped test specimen.

The kinematic calibration approach with the MSVD method and VP method could be successfully applied to the 3-DOF parallel tool head and other 3-DOF parallel mechanisms.

An interferogram is produced by modulating the difference between the extraordinary refractive index and the ordinary refractive index for photoelastic crystals in photoelastic-modulated Fourier transform spectrometers (PEM-FTs). Due to the influence of the refractive index dispersion characteristics on the maximum optical path difference of the interferogram, it is necessary to study wavelength calibration methods.

A wavelength calibration method for PEM-FTs was proposed based on the modulation principle of the photoelastic-modulated interferometer and the relationship between the maximum optical path difference and the refractive index difference. A 632.8 nm narrow-pulse laser was used as a reference source to measure the maximum optical path difference () of the interferogram, and the parameter was used to calculate the discrete frequency points in the frequency domain. To account for the influence of refractive index dispersion on the maximum optical path difference, the refractive index curve for the photoelastic crystal was used to adjust the discrete frequency coordinates.

The error in the reconstructed spectral frequency coordinates clearly decreased. The maximum relative error was 2.5%. A good solar absorption spectrum was obtained with a PEM-FT experimental platform and the wavelength calibration method.

The interferogram is produced by adjusting the difference between extraordinary refractive index and ordinary refractive index for the photoelastic crystal in the PEM-FTs. Given the wavelength dependence on the refractive indices, in view of the modulation principle of the photoelastic modulated interferometer, the relationship between the maximum optical path difference and the refractive index difference, the variation law of the refractive index of the photoelastic crystal and the process of spectral reconstruction is presented in this paper.

The purpose of this paper is to accurately obtain the deformation of a hybrid robot and rapidly enable real-time compensation in friction stir welding (FSW). In this paper, a prediction algorithm based on the back-propagation neural network (BPNN) optimized by the adaptive genetic algorithm (GA) is presented.

Via the algorithm, the deformations of a five-degree-of-freedom (5-DOF) hybrid robot TriMule800 at a limited number of positions are taken as the training set. The current position of the robot and the axial force it is subjected to are used as the input; the deformation of the robot is taken as the output to construct a BPNN; and an adaptive GA is adopted to optimize the weights and thresholds of the BPNN.

This algorithm can quickly predict the deformation of a robot at any point in the workspace. In this study, a force-deformation experiment bench is built, and the experiment proves that the correspondence between the simulated and actual deformations is as high as 98%; therefore, the simulation data can be used as the actual deformation. Finally, 40 sets of data are taken as examples for the prediction, the errors of predicted and simulated deformations are calculated and the accuracy of the prediction algorithm is verified.

The entire algorithm is verified by the laboratory-developed 5-DOF hybrid robot, and it can be applied to other hybrid robots as well.

Robots have been widely used in FSW. Traditional series robots cannot bear the large axial force during welding, and the deformation of the robot will affect the machining quality. In some research studies, hybrid robots have been used in FSW. However, the deformation of a hybrid robot in thick-plate welding applications cannot be ignored. Presently, there is no research on the deformation of hybrid robots in FSW, let alone the analysis and prediction of their deformation. This research provides a feasible methodology for analysing the deformation and compensation of hybrid robots in FSW. This makes it possible to calculate the deformation of the hybrid robot in FSW without external sensors.

The purpose of this paper is to demonstrate how food waste management can affect both retail and distribution operators’ efficiency performance and their ability to create value. In particular, the paper shows how optimizing food waste management characterizes best practices and favors the development of sustainability.

Based on a survey of 196 outdoor market operators (including farmers and street food traders) from 27 outdoor markets, the authors analyzed unsold food/food wastage processes vis-à-vis the operators’ behavior and attitude. To provide accurate definitions of the satisfaction levels, a consumer perception survey was carried out, with a usable sample of 2,107 questionnaires. The efficiency performance was evaluated according to data envelopment analysis.

The results showed that farmers operate more efficiently than street food traders and that the traditional management of unsold food/food waste is an important competitive element in this sector.

The sample represents the Greater Turin Area in Italy, i.e., thus, limiting generalizability of the results. In addition, the variables analyzed were limited to certain aspects of selling processes and food waste management.

The results provide some indicators on how a more rational style of unsold food management can improve an operators’ performance and help make a social impact.

To the best of the authors’ knowledge, this is the first study that analyses outdoor market operators’ efficiency, based on the use of food waste as a variable affecting their performance.

Reports on the first of two joint symposia to be held in South China during 1998. The Zhongshan University Symposium focused on library automation and networking, with six sessions on specific subthemes and 47 papers on such topics as information resources development and digital libraries, Internet information applications and services, resource sharing and regional cooperation. Participants at the symposium concluded that the standardisation of a Chinese encoding system to cater for all Chinese characters from China, Taiwan, Japan and Korea is a prerequisite for future cooperation and resource sharing. In addition, the panellists agreed that it is important to concentrate on developing library and information networks, especially using Internet technology and related resources.