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In the current literature, there is little systematic research on the relationship among adjustment of the income distribution, change in economic structure and improvement of macroeconomic efficiency.

This paper expands Marx's reproduction schema into the “Marx–Sraffa” three-department structure table comprising fixed capital, general means of production and means of consumption and employs China's input–output table from 1987 to 2015 to portray the relationship between income distribution and macroeconomic efficiency under investment-driven growth.

This paper calculates the wage–profit curve of China's economy and evaluates the space of macroeconomic efficiency improvement in China based on the deviation between actual and potential income distribution structure.

The results show that there is a downward trend of the profit rate, which meets Marx's theoretical prediction, and the decline in the profit rate is mainly attributed to an increase in the organic composition of capital arising from the rapid growth of fixed capital investment under extended growth. The analysis of macroeconomic efficiency shows that the space for improving macroeconomic efficiency is extremely limited under traditional growth pattern and that China must transform its economic development pattern and foster new economic growth drivers.

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research.

In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method.

This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method.

Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment.

This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.

The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied.

This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies.

The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed.

This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

This research aims to grasp hotel guests' motives and potential benefits sought when interacting with other guests, service personnel and residents and examines how these benefits can contribute to the total guest experience.

Mixed methods are adopted for the purpose of this study comprising individual interviews and a questionnaire survey.

Five groups of advantages emerge from individual interviews, including friendliness in interaction, social benefits, information acquisition, curiosity gratification and hospitality services. In the survey, which gathers 326 questionnaires, this study reveals that the five types of benefits derived from hotel guests' interactions could be further categorized into two dimensions: civility (e.g. friendliness and social) and utility (e.g. information, curiosity and service). The study confirms that four out of five potential or expected benefits from this personal interaction is significantly associated with the total hotel experience.

Respondents of this study are culturally homogenous; as a result, multi-cultural settings should be considered for future research.

Tourism and hospitality literature on people's interaction is mostly center around social aspects of interaction. The current study comprehensively explores all expected utilities of interaction, occurring in all sorts of interactions (e.g. customer-to-resident and customer-to-service personnel). Specifically, the findings of this study uncover the underlying factors which prompt the tourists to interact with other people in a lodging setting and examine the relative importance of those underlying factors to the total lodging experiences.

Social media management is an emerging profession that is growing as companies increasingly adopt social media. The purpose of this paper is to analyze social media managers’ personal branding.

In-depth qualitative data is drawn from 20 semi-structured interviews with social media managers and supported by three years of orienting fieldwork in Toronto, Canada.

Social media managers are responsible for managing and executing organizations’ brands and presence on social media and digital platforms. As lead users of social media, social media managers provide critical insight into the emerging practices of personal branding on social media. “The future audience” is introduced to describe how individuals project a curated brand for all future unknown and unanticipated audiences, which emphasizes a professional identity. Due to workplace uncertainty, social media managers embody the mentality of being “always-on-the-job-market”, which is a driver for personal branding in their attempt to gain or maintain employment.

While personal branding is largely discussed by industry professionals, there is a need for empirical research on personal branding that examines how various employee groups experience personal branding. This research fills this gap by analyzing how people working in social media brand their identity and how their personal branding is used to market themselves to gain and maintain employment. The development of “the future audience” and “always-on-the-job-market” can be used to understand other professions and experiences of personal branding.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

The purpose of this paper is to identify the components of logistics value and examine their influence on customer satisfaction in e-commerce. This study investigates the moderation effect between those two variables using the overall service level in the different industries of e-commerce.

A total of 592 correctly filled questionnaires from telephone and web interviews (computer-assisted telephone interviews and computer-assisted web interviews) were scrutinized. Hierarchical linear modeling (as a part of a wider group of multilevel modeling studies) was used to verify the dependencies between variables from an organization and industry levels.

The logistics factors indicated and described in the paper differently affect the value for the customer. This value is subjective and dynamic. For this reason, the online seller should develop a system to create a sustainable value proposition. It is plausible due to the possibility of choosing the type of delivery, date of collection and change thereof, as well as that of returning the product. Because of all this, the customer decides on the way of the order execution and creates the value chain.

The developed model is aimed at identifying universal relationships that create the customer satisfaction mechanism for the logistics value. However, this may result in other aspects of customer satisfaction being neglected. The authors are aware that the creation of value by a company in e-commerce must be approached in a systematic manner.

The results obtained and the representativeness of the surveyed sample of companies lead to the formulation of implications for business practice. The conclusions of the research definitely indicate a need to build awareness of logistics value and its influence on customer satisfaction through the service level in the industry. Because of the identified components of the logistics value and industry characteristics, managers of online retailers can better run their businesses, increase customer satisfaction, and thus improve their performance.

It is the first study that concerns e-commerce in individual industries, with particular emphasis on logistics and its impact on customer satisfaction.