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Since the UK Companies Act 1981, different reporting standards have developed for different classes of company to reduce the reporting burden on non-listed companies. There are now different regimes for listed, large private, medium-sized, small and micro companies. This strategy raises the issue of whether earnings quality across the different classes of company is comparable. The paper aims to discuss this issue.

The paper uses the smoothness of earnings to measure reporting quality across the different types of companies from 2006 to 2013, based on 514,000 observations. Smoothness is an indicator of poor quality.

The authors find that listed companies have the highest earnings quality, closely followed by small and micro companies. In contrast, large private and medium-sized companies have much lower earnings quality. Overall, the authors find companies which switch between reporting regimes have lower earnings quality. The authors also find that earnings quality is not affected by the small company exemption from audit.

Companies filing abbreviated accounts are excluded since they do not file an income statement. The recent revisions to UK GAAP (FRS 102 and FRS 105) are not examined due to insufficient data.

The Financial Reporting Council’s (FRC) strategy of reducing the financial reporting and auditing obligations for small companies seems not to have significantly affected earnings quality. However, the FRC may need to review the reporting requirements of large private and medium-sized companies and also the option of companies to switch between reporting regimes; in these settings earnings quality appears to be weaker.

The paper studies the effect of earnings quality across the different reporting regimes in the UK. Novel and important features of the study are that the sample covers a wide variety of small and micro companies which have not been analyzed previously; the results are disaggregated by year, for assurance that the results are not driven by a single rogue year; and the authors also address the small company exemption from audit, and the flexibility of non-listed companies to switch between regimes.

This study investigates the interrelationships between competitions in different banking markets and shadow banking for the Chinese banking industry over the period 2003–2017. The current study also examines the determinants of competition in different banking markets and the factors influencing the size of shadow banking.

Bank competition is measured by the Boone indicator, while the relationship between bank competition and shadow banking is examined through a three-stage least square estimator.

The findings suggest that a larger volume of shadow banking leads to a decline in the level of competition in the deposit market, loan market and noninterest income market, while an increase in the level of competition in the loan market, deposit market and noninterest income market leads to an expansion of shadow banking. The authors find that higher bank risk and higher developed of stock market reduce the competitive condition in the loan market, and the competition in the deposit market will be enhanced by higher levels of banking sector development and higher levels of inflation, but bank diversification will reduce the level of competition in the deposit market. The authors further find that higher bank profitability and higher stock market development reduce bank competition in the noninterest income market. Finally, the results show that larger bank size and higher development of stock market reduce the size of shadow banking in China, but higher economic growth increases the size of shadow banking.

This is the first piece of research investigating the relationship between bank competition and shadow banking. This will also be the first piece of research examining the determinants of competition in different banking markets and also the factors influencing the size of shadowing banking in China.

Chief Executive Officer (CEO) activism, i.e. executives, publicly weighing in on sociopolitical debates, is an area of increasing interest in academia and business. This young research field provides valuable insights, but it still represents a scattered discussion in a variety of disciplines. Thus, this paper aims to present a guiding framework, integrate current knowledge, aggregate published findings and outline avenues for future research.

The authors conducted a systematic literature review building on a sample of 36 publications. In consequence, 1,146 lead themes were derived and studied in an in-depth qualitative analysis by deploying a pattern-inducing method.

Research on CEO activism can be placed on a time-oriented logic, giving insights into the realisation of activism, stakeholder reactions, moderators and perception effects. These four aggregate dimensions can be explained by 15 second-order themes and 48 more detailed first-order themes.

Considering the risks and benefits of CEO activism, top executives and communication professionals should be aware of its implications. This paper provides an integrated view of the different mechanisms and potential effects of CEO activism. Thereby, it proposes communicative planning from activism’s realisation to its perceptual results.

The study provides a holistic view of CEO activism as a starting point for further discussion. To the latest of the authors’ knowledge, this work is the first integrated conceptualisation of the discussion of CEO activism. The proposed avenues for future research stem from a detailed examination of published knowledge.

The role of chief executive officer (CEO) personal characteristics in shaping corporate policies has attracted increasing academic attention in the past two decades. In this review, the authors synthesize extant research on CEO attributes by reviewing 232 articles published in 29 journals from the accounting, finance and management literature. This review provides an overview of existing findings, highlights current trends and interdisciplinary differences in research approaches and identifies potential avenues for future research.

To review the literature on CEO attributes, the authors manually collected peer-reviewed articles in accounting, finance and management journals from 2000 to 2021. The authors conducted in-depth analysis of each paper and manually recorded the theories, data sources, country of study, study period, measures of CEO attributes and dependent variables. This procedure helped the authors group the selected articles into themes and sub-themes. The authors compared the findings in various disciplines and provided direction for future research.

The authors highlight the role of CEO personal attributes in influencing corporate decision-making and firm outcomes. The authors categorize studies of CEO traits into three main research themes: (1) demographic attributes and experience (including age, gender, culture, experience, education); (2) CEO interactions with others (social and political networks) and (3) underlying attributes (including personality, values and ideology). The evidence shows that CEO characteristics significantly affect a wide range of specific corporate policies that serve as mechanisms through which individual CEOs determine firm success and performance.

CEO selection is one of the most crucial decisions made by corporations. The study findings provide valuable insights to corporate executives, boards, investors and practitioners into how CEOs’ personal characteristics can impact future firm decisions and outcomes that can, in turn, inform the high-stake process of CEO recruitment and selection. The study findings have significant practical implications for corporations, such as contributing to executive training programs, to assist executives and directors attain a greater level of self-awareness.

Building on the theoretical foundation of upper echelons theory, the authors offer an integrated theoretical framework to consolidate existing empirical research on the impacts of CEO personal attributes on firm outcomes across accounting and finance (A&F) and management literature. The study findings provide a roadmap for scholars to bridge the interdisciplinary divide between A&F and management research. The authors advocate a more holistic and multifaceted approach to examining CEOs, each of whom embodies a myriad of personal characteristics that comprise their unique identity. The study findings encourage future researchers to expand the investigation of the boundary conditions that magnify or moderate the impacts of CEO idiosyncrasies.

The purpose of this paper is to study the effects of multidimensional friendship networks on economic outcomes in the domain of online people-to-people (P2P) lending markets.

The empirical analysis is based on the data set of transactions and friendship networks from PPDai.com market, the most prominent P2P lending market in China. A friendship hierarchy is proposed in this paper to conceptualize friendship network types. Furthermore, methodologies of t-test, logistic regression and ordinary least squares regression are implemented to measure the impact of multidimensional friendship network variables on the probability of successful funding, as well as the interest rates on funded loans.

The study demonstrates significant effects of structural, relational and cognitive friendship networks using PPDai.com data. The results indicate that structural friendship network measured in terms of the number of friendship ties is a significant factor of funding performance. Additionally, borrowers, who are involved in higher-quality friendship networks, are more likely to be funded and pay lower interest rates on funded loans. Also, the deeper the level of the relationship is in the friendship hierarchy, the more significant will be the effect of friendship on the final economic results. Furthermore, quality is more important than quantity in determining funding performance.

This paper is the first to study the effects of multidimensional friendship networks on economic outcome variables in the domain of online P2P lending, thus broadening the theory of multidimensional social capital, which can deepen our understanding about how social networks work and have significant implications practically and theoretically.

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.

For high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.

The proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).

From a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.

The originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

In recent years, the concept of subculture has been fiercely criticized, with some scholars even claiming that it is no longer relevant in a multi-cultural world (Muggleton, 2000; Chaney, 2004; Stahl, 2004). However, the authors argue that by revisiting the Chicago School tradition and reconceptualizing subculture on the basis of acknowledging its limitations and its potential, subculture theory remains applicable in the context of contemporary China. Through an eight-month ethnographic study of a group of deviant students in a secondary school in urban China, the purpose of this paper is to contend that the subculture of these young people from lower-class backgrounds is a means to negotiate their space and power in a failing school system situated in a drastically transforming society full of diversified yet often conflicting values.

In this study, the authors undertook an ethnographic study to follow a group of deviant students for eight months, trying to understand their everyday lives and the process of their identity construction. The research was conducted in Xiamen, a coastal city located in the southeast part of mainland China. Unlike large metropolitan areas such as Beijing and Shanghai, where most studies have been conducted so far, Xiamen represents one of the medium-sized cities, which are the majority in China. After a process of sampling among 11 classes from five schools in different tiers, the authors chose one class in Grade 2 at a medium-level secondary school called “Central Park Secondary School” as a pseudonym. The authors stayed in the field for the main study and the authors also paid another visit to the school to follow up on students’ recent development.

In this study, a group of problem students identified with each other and shared the same problems and situations, and collectively formed a subcultural group, from within which they could challenge the authority of teachers and parents and negotiate power in the school; for example, reaching a truce with teachers so that they could have an easier time at school until they graduated. Their subculture and resistance may seem like a self-defeating practice, because what they learned at school and the qualifications they obtained could only assure them laboring jobs and reproduce their lower class status. However, this subculture offered an alternative way to safeguard their happiness and healthy development, which in this case is psychological well-being and better interpersonal skills.

This paper could provide the teachers and school administrators with a new perspective to look at some of their students’ poor performance and disruptive behaviors. With a deeper understanding of their “deviant” students, the teachers may develop more pertinent measures to help their students.

This paper argues that, through revisiting the Chicago School tradition and reconceptualizing subculture on the basis of acknowledging its limitations and potential, subculture theory remains applicable in the context of contemporary China.

The purpose of this paper is to improve the nutritional value of chicken nuggets by partial substitution of animal fat with palm stearin. Three nugget formulations with the fat level of 10.3 per cent palm fats consisted of blends from Olein: Stearin at ratios of 30:70, 50:50, 70:30 were used to replace chicken skin (control). Palm fat treatments resulted in a significant decrease of cholesterol content.

Four nugget formulations with the fat level of 10.3 per cent palm fats consisting of blends from Olein: Stearin at ratio of 30:70, 50:50, 70:30 and a commercial shortening, Socfat 36 are studied. The same formulation using chicken skin as a control and a commercial brand of nugget is used as a comparison. Proximate analysis of raw and cooked palm fat nuggets showed a decrease in the protein content and an increase of the fat content. The cholesterol content were reduced up to 45.9 per cent through the addition of palm fat, when compared against the control treatment. Fatty acid composition of palm fats in the palm substituted formulations increased the level of C16:0 and decreased C16:1, C18:1, C18:2, compared with fat from chicken skin.

The cholesterol content was reduced by 45.9 per cent when chicken skin and fat were substituted with palm fats. The texture of chicken nugget increased when added with palm fats. Palmitic acid (C16:0) content increased while palmitoleic acid (C16:1), oleic (C18:1) and linoleic acid (C18:2) decreased in palm fat treated nuggets.

The paper is of value in showing how palm stearin and olein usage in chicken nuggets helps reduce the product's cholesterol content.

When CEOs are publicly weighing in on sociopolitical debates, this is known as CEO activism. The steadily growing number of such statements made in recent years has been subject to a flourishing academic debate. This field offers first profound findings from observational studies. However, the discussion of CEO activism lacks a thorough theoretical grounding, such as a shared concept accounting for the heterogeneity of sociopolitical incidents. Thus, the aim of this paper is to provide an archetypal framework for CEO activism.

The authors used a multiple case study approach on 145 activism cases stated by CEOs and found seven distinct statement archetypes.

The study identifies four main structural design elements accounting for the heterogeneity of activism, i.e. the addressed meta-category of the statement, the targeted outcome, the used tonality and the orientation of the CEOs’ positions. Further, the authors found seven distinguishable archetypes of CEO activism statements: “Climate Alerts”, “Economy Visions”, “Political Comments”, “Self-reflections and Social Concerns”, “Tech Designs”, “Unclouded Evaluations” and “Descriptive Explanations”.

This typology classifies the heterogeneity of CEO activism. It will enable the analysis of interrelationships, mechanisms and motivations on a differentiated level and raise the comprehensibility of research-results.

The framework supports executives in understanding the heterogeneity of CEO activism and to analyse personality-fits.

To the authors’ knowledge, this marks the first conceptualisation of activism developed cross-thematically. The work supports further theory-building on CEO activism.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.