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Recent research has proposed a specific female phenotype within autism spectrum disorder (ASD). It suggests females exhibit differences in social communication styles with higher levels of camouflaging and compensatory strategies, as well as variance in restrictive repetitive behaviours (RRBs); however, many existing studies have been based on either small, disproportionate or child and adolescent samples, leaving questions about the specific phenotype. This study aims to explore the sex difference and phenotype in a clinic sample of individuals diagnosed with autism.

A service evaluation of sex/ gender differences on 150 historical ASD assessment reports (75 males, 75 females) using a 103-item questionnaire developed from a quantitative review of existing literature was undertaken.

Females camouflaged more significantly than males in five different areas (thinking how to act next, preparing conversation in advance, making lists of prompts/social responses, wearing a mask/acting, less monotone voice); however, these were not maintained in post-analysis correction.

This study points the evidence towards a different phenotype of Autism that is more common in women than men rather than a unique female phenotype.

This paper aims to systematically review the field of non-financial reporting (NFR) in hybrid organizations, focusing on state-owned enterprises, third-sector organizations and public–private partnerships. This is a timely attempt to identify the state of the art in the literature and outline the future research agenda. The paper answers two research questions: RQ1. What can be learned about NFR in hybrid organizations from the existing literature? RQ2. What are the future avenues for research on the topic?

A systematic literature review method was applied in this paper to summarize evidence from extant literature on NFR in hybrid organizations. The Scopus and Web of Science Core Collection databases were used to locate 92 articles for the review.

Recent years have witnessed a sharp increase in the number of articles on the topic. Regarding the implications of NFR for hybrid characteristics, NFR has some potential to strengthen the influence of non-market (i.e. state, community and social) logics in hybrid organizations. However, this potential may be limited due to the effect of market logics and the tensions that arise between the multiple logics in hybrid organizations. Regarding the implications of hybrid characteristics for NFR, these characteristics can not only affect the extent, the quality, the likelihood and the institutionalization of NFR but also result in the development of new NFR frameworks. The review calls for more research on the implications of NFR for multiple institutional logics and the implications of these logics for NFR in hybrid organizations.

To the best of the authors’ knowledge, this is the first literature review that mobilizes insights from hybridity research to analyze NFR literature on diverse hybrid organizations.

This paper aims to examine the process for estimation of efforts for software development and suggests a framework for estimating software development costs and ensuring quality of code in e-Government projects from the Indian state of Andhra Pradesh. With no established processes for estimation of efforts, the Government relied on open bids from the market to develop these e-Government applications.

The paper adopts an exploratory case study approach to analyze the e-Government applications in Andhra Pradesh. Using data from the information technology department of the Government of Andhra Pradesh, the paper evolves a framework to compute costs of software development, based on the software development life cycle.

The framework helps in arriving at a hurdle price before the tender process. The study has shown that an e-Government application in AP state would cost Rs. 224,000, or US$2,969.25, for a simple application, and Rs. 33,60,000, or US$44,538.71, for a complex application over a five-year period, depending on the complexity and size of the application. This information would be useful to the Government decision-makers for expanding e-Government.

Further research may assess the utility of this framework for e-Government support activities like automation of data centers, video conferencing facilities and ushering in financial technologies for encouraging cashless payments.

The paper provides information that could be of value at a national level (for India) and at the same time providing a guide for other countries that would like to adopt this framework.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

This paper aims to examine the influence of sustainability assurance report format (separate versus combined with financial information assurance) and level (limited versus reasonable) on nonprofessional investors’ judgments.

This study uses a 2 × 2 between-participants experiment with 436 US nonprofessional investors. The authors manipulate sustainability assurance report format and level to identify differences in judgments of information credibility, investment desirability and investment amount.

This study finds that sustainability assurance level influences participants’ judgments only when the financial and sustainability assurance reports are presented separately. Specifically, participants assess sustainability performance information as more credible and make higher investment judgments when presented with a separate limited, as opposed to reasonable, assurance sustainability report.

The International Auditing and Assurance Standards Board expressed concerns regarding whether assurance reports accompanying emerging forms of extended external reporting (EER) effectively communicate the level of assurance provided by the independent practitioner. The result that assurance level does not influence investor judgments in the combined reporting format appears contrary to the idea that integrated reporting should provide connectivity between financial and sustainability information. The finding that investors make higher investment and credibility judgments with limited assurance is inconsistent with the intent of sustainability assurance professional guidance and recent research results. Together, the findings suggest that investors may not be able to distinguish between differing levels of sustainability assurance when this information is presented in a combined report format.

Standard setters should consider how sustainability assurance report format and assurance level impact nonprofessional investor judgments.

Research on the effects of EER assurance report format is sparse. The results indicate that even slight changes in assurance report wording may cause investors to perceive that a limited assurance report conveys a higher assurance level than a reasonable assurance report.

Underpinned by the fit-fluency framework, this research aims to explore the effect of visual entropy (i.e. the neatness or disorder of food presentation) on the likelihood to purchase under different time-related positioning conditions.

Two experiments were conducted with customers who are located in the USA via Amazon Mechanical Turk. Study 1 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four advertisements for a fictitious ice cream brand. Study 2 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four book covers for fruit salad recipes.

The findings demonstrate low entropy (i.e. neatness) increases purchase likelihood when being paired with modern positioning, whilst high entropy (i.e. non-neat presentation) positively influences the propensity to purchase a traditional product on account of temporal fit. These relationships are mediated by perceived quality and nostalgia.

This research extends the understanding of visual entropy and addresses the inconclusive evidence of the impact of the neatness of product presentation on consumer behavior. The authors elucidate the mechanisms behind which neatness and non-neatness of food presentation affect purchase likelihood when different types of time-related positioning are featured.

This study investigates the effect of corporate governance mechanisms and country-level factors on the extent of Internet Financial Reporting (IFR). We used a sample of 106 listed firms from five African countries. A financial reporting disclosure index was used to compute the aggregate IFR scores, which are made up of two components: content and presentation. Our results indicate that IFR relates to board size, firm size, country-level governance, economic development and index return. These results evidence the predominance of country-level factors over firm-specific factors in explaining the extent of IFR in Africa. It also shows that corporate governance mechanisms via board practices are insufficient to explain IFR in Africa. By further extending our analysis into the two components of IFR, we find that factors affecting the content and presentation dimensions are different. This study is among the first to investigate the extent of IFR in several African countries and adds to the existing evidence that has mainly focussed on firm-specific factors.

This chapter explores the presentation of women's violence in Tamil mega serials. Tamil mega serials are produced in India and aired six days a week on satellite television channels. The story revolves around households with extended families living together and issues affecting women such as family well-being, motherhood and fertility. Women mostly take the role of the main protagonist and antagonist in Tamil serials. This chapter analyses the presentation of violence in 10 episodes of Chandralekha, a Tamil mega serial. Perpetrators of violence in Tamil serials are mainly female antagonists and other characters supporting the antagonists. The rivalry between the protagonist and antagonist centres around the struggle for property or the love of or marriage with a man. The type of violence ranges from mild to severe kinds of physical violence, and non-physical violence. The presentation of violence in Tamil serials reflects gender inequality in society. The meaning of some forms of violence in mega serials is closely related to the traditional gender roles and notion of traditional femininity in society.

Despite the significance of online communication and interactions, previous research has not systematically compared all features on a single platform from the users' perspective. This study aims to fill this gap by extensively reviewing the current literature on social media affordances and proposes and tests a feature-centric and affordance-based conceptualization of social media platforms (SMPs) between users, features, the audience and content.

This research surveys users on Facebook, one of the largest SMPs, and asks them to assess 20 features of Facebook on six relational affordances between users, features, audience and content. The data in this study were collected on Amazon Mechanical Turk (MTurk) with participants from the US Correspondence analysis was employed to examine the relationship between affordances and the ties among affordances, features and outcomes.

Results of the study indicate that users perceive features differently, and employing features as the unit of analysis captures users' interactions effectively. The findings support the presence of user-oriented affordances, such as presentation flexibility, association and content association. These three affordances can be summarized in two higher-level ones: self-expression and connection (SEC) and persona-linked content (PLC). Our findings of the two dimensions, SEC and PLC, highlight the importance of targets and their connections in understanding social media interactions' dynamic nature.

By proposing to shift the focus from platforms to features, this study suggests that companies should focus on understanding the features they use for their users to interact with their brand, rather than merely ensuring that their company is omnipresent on all platforms. This study underlines the need to focus on features that will help managers influence interpersonal and user-brand communications and interactions on social media.

This research is the first to put features at the center of its investigation and quantitatively examine the relationship between social media features and affordances in a social media context. In all, this research provides a new unit of analysis that is more suitable for researchers to build a robust conceptual foundation for affordances. We believe that conceptualizing audience and content as outcomes, distinguishing it from features and creating connections between them as affordances is the unique aspect of our conceptualization.

Audio-visual presentations – delivered either in real-life or virtually – feature heavily in educational assessments and employer recruitment. This study explored neurodivergent undergraduate students' experiences of presentations. The aim was to understand how neurodivergent students describe experiences of presentations in educational and workplace contexts and how neurodivergent students experienced training, support activities and learning technologies associated with presentations.

An exploratory qualitative phenomenological approach was taken, from students' perspectives. Overall, 12 neurodivergent undergraduate students (M_age = 21.89 years, SD_age = 2.57; nine women, two men, one non-binary) discussed their experiences of presentations within educational and/or professional contexts via semi-structured remote interviews. The sample included individuals with diagnoses of anxiety, depression, dyslexia, borderline personality disorder, dyscalculia, dyspraxia, and panic disorder.

Thematic Analysis of interview transcript data revealed four main themes (with sub-themes in parentheses): Control (preparedness; delivery); Audience Perceptions and Behaviours (expectations of “normality”; shared knowledge; audience “expertise”); Intervention Efficacy (early access; individuality; learning technologies) and Value of Presentation Skills (reciprocity between education – workplace; self-efficacy; self-esteem; learner development).

The dataset was extracted from a relatively small sample from a single university and indeed a single academic discipline. Furthermore, the dataset was collected during the ongoing COVID-19 pandemic – although this gives us a valuable snapshot of students' experiences and perceptions during this time, whether the author can extrapolate these findings in future is unclear.

The findings help understand how we better support students. Better ways to support learners can be developed in developing presentation and audience skills. This research shows that alternative assessment provisions must be based on individuals and their own specific needs and skills, rather than their divergence label. This research can inform the development of digital learning technologies.

This research can inform how educators, coaches, trainers, and facilitators “train” audiences to be more inclusive and less prejudicial/biased. We can understand how to better construct social spaces for presentations, in the classroom and the world of work.

This report presents a valid and valuable methodological approach, conducted and reported transparently. This research was conducted during a crucial, unprecedented and precarious time period for learners and education professionals. Implications are considered with respect to the design of teaching, learning and assessment activities; facilitator, learner, and peer behaviours; the role of digital learning technologies; and employment/employability.