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The purpose of this study is to question the undifferentiated treatment of individual traders as “dumb noise traders?”. We question this undifferentiated verdict by conducting an analysis of the cognitive competence of individual investors.

The authors let experts (both experienced researchers as well as practitioners) assess the mathematical and verbal reasoning demands of investment tasks investigated in previous studies.

Based on this assessment, this paper concludes that individual investors are able to perform a number of complex cognitive actions, especially those demanding higher-order verbal reasoning. However, they seem to reach cognitive limitations with tasks demanding greater mathematical reasoning ability. This is especially unfortunate, as tasks requiring higher mathematical reasoning are considered to be more relevant to performance. These findings have important implications for future regulatory measures.

This study has two non-trivial limitations. First, indirect measurement of mental requirements does not allow authors to make definite statements about the cognitive competence of individual investors. To do so, it would be necessary to conduct laboratory experiments which directly measure performance of investors on different investment and other cognitively demanding tasks. However, such data are not available for retail investors on this market to the best of the authors’s knowledge. We therefore think that our approach is a valuable first step toward understanding investors’ cognitive competence using data that are available at this moment. Second, the number of analyzed (and available) tasks is rather low (n = 10) which limits the power of tests and restricts the authors from using more profound (deductive) statistical analyses.

This paper proposes to illustrate information in key investor documents mostly verbally (e.g. as proposed by Rieger, 2009), compel exchanges and issuers of retail derivatives to create awareness for the results of the reviewed studies and our conclusion and to offer online math trainings especially designed for individual investors to better prepare them for different trading activities, as these have been shown to be as effective as face-to-face trainings (Frederickson et al., 2005; Karr et al., 2003).

This study can only be considered as a first step toward understanding the cognitive limitations of individual investors indirectly and could be transferred to other market areas as well.

This study is the first to combine the assessment of outstanding researchers in this field with the results of previous studies. In doing so, this paper provides an overarching framework of interpretation for these studies.

The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.

This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity. A constraint handling technique based on feasibility and sum of constraints violation is adopted. Also, a special technique to handle equality constraints is proposed.

The paper shows that it is possible to improve PSO and keeping the advantages of its social interaction through a simple idea: perturbing the PSO memory.

The proposed algorithm shows a competitive performance against the state‐of‐the‐art constrained optimization algorithms.

The proposed algorithm can be used to solve single objective problems with linear or non‐linear functions, and subject to both equality and inequality constraints which can be linear and non‐linear. In this paper, it is applied to various engineering design problems, and for the solution of state‐of‐the‐art benchmark problems.

A new neighborhood structure for PSO algorithm is presented. Two perturbation operators to improve PSO algorithm are proposed. A special technique to handle equality constraints is proposed.

With multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.

Detailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.

First, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.

First, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.

This study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.

This study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

The paper discusses the prediction of shirt patterns for different body sizes using multiple linear regression (MLR).Design/methodology/approach – A total of 29 pattern parameters from men's tailor‐made shirt and 34 body parameters obtained from a body scanner were designed for analysis. MLR has been applied to examine the underlying relationship between shirt pattern parameters and body measurements.Findings– Compared with formulae from the pattern expert, the prediction of shirt pattern from MLR has been improved.Originality/value – The findings could help to predict pattern size with different body sizes more accurately.

This paper investigates the impact of line of business and geographical segments information disclosure on the firms' perceived risk when either of them is disclosed for the first time without prior segmental information. British data for both treatment and control groups were utilized and a dummy variable technique was employed in the study. The results show that the dummy variables in the treatment groups (line of business and geographical segments) were significant, but insignificant in the control group. The results indicate that the disclosure of line of business and geographical segment information does have an impact on a firm's perceived risk.

Big 4 professional services firms increasingly lay claim to recruiting and including staff of diverse genders, cultures, ages and sexualities. Drawing on Foucauldian insights, this study explores how LGBTIQ+ staff navigated shifting technologies of client power, at the time marriage equality was legislated in Australia.

This article explores changing experiences of LGBTIQ+ staff and allies, through 56 semi-structured interviews undertaken through 2018–2019.

Technologies of client power were central to shaping workplace experiences for LGBTIQ+ staff. However, each firm was also keen to carve unique and bold responses to changing societal attitudes regarding sexuality and gender. These progressive moves did not sit comfortably with all clients, and so this article provides insight into the limitations of client privilege within professional services firms. For staff, this increasing complexity of sometimes opaque, contradictory and shifting technologies of client and firm power, enabled agency to explore a sense of self for some, but continued to exclude others.

Little attention has been directed to exploring challenges for staff of sexual and gendered diversity within professional services firms, or to exploring how staff navigate changing perceptions of client power.

Resurgent interest in the life and work of the Italian Cambridge economist Piero Sraffa is leading to New Directions in Sraffa Scholarship. This chapter introduces readers to some of these developments. First and perhaps foremost is the fact that as of September 2016 Sraffa’s archival material has been uploaded onto the website of the Wren Library, Trinity College, Cambridge University, as digital colour images; this chapter introduces readers to the history of these events. This history provides sharp relief on the extant debates over the role of the archival material in leading to the final publication of Production of Commodities by Means of Commodities, and readers are provided a brief sketch of these matters. The varied nature of Sraffa scholarship is demonstrated by the different aspects of Sraffa’s intellectual legacy which are developed and discussed in the various entries of our Symposium. The conclusion is reached that we are on the cusp of an exciting phase change of tremendous potential in Sraffa scholarship.

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and the expanded role of consumers.

The study drew on online archival data from the AirbnbHell.com website, where people share their stories about their Airbnb-related negative experiences. The authors reviewed 405 hosts’, guests’ and neighbours’ stories and coded the identified forms of misbehaviours into categories. The typology thus developed was validated in the context of the Uber Rides service.

User misbehaviours in the SE context can be distinguished based on the domain in which the user role is violated and the nature of violated norms. These two conceptual distinctions delineate a four-fold typology of user misbehaviours: illegal, unprofessional, unbefitting and uncivil behaviours.

The trustworthiness of the stories could not be assessed.

The presented typology can be used as a mapping tool that facilitates detection of the full scope of misbehaviours and as a managerial tool that provides ideas for effective management of misbehaviours that correspond to each category.

The paper presents the first empirically derived comprehensive typology of user misbehaviours in SE settings. This typology enables classification of a broad set of misbehaviours, including previously overlooked unprofessional behaviours carried out by peer-service providers. The study also puts forward a revised definition of consumer misbehaviours that encompasses the impact of misbehaviours on parties not directly involved in the SE-mediated exchange.