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Non-gated residential communities (NGR) are now becoming significant in Jordan resulting in an increase in low and medium-income areas. This study aims to investigate the sense of community at residential level within NGR by testing the characteristics presented in the first and largest non-gated community in Jordan (Al-Sharq project).

Such characteristics were identified via literary reviews and visual data collected through site visits, observation and photographs of the project's physical settings. This formed the basis of a questionnaire/survey that was distributed to the residents. This research depends on the mixed-method approach (qualitative and quantitative) to achieve the research objectives. The quantitative method involved the use of a questionnaire/survey, while the qualitative method undertook a comparative process using some statistical methods for the main characteristics. The results were analysed by using descriptive statistics, comprising frequency and factor analyses.

The study concludes with a framework consisting of suggestions and recommendations to remove the main constraints on improving the quality of life for the non-gated residential community.

The outcome of this study will influence the decisions made by the parties involved in urban development in Jordan when designing residential neighborhoods.

The significance of this paper is that while the majority of studies have been on the evaluation of gated communities in developing countries, there have only been a limited of studies specifically examining the experience of residents in those environments. Therefore, this paper contributes and adds to the existing knowledge in the development of non-gated communities in a developing country.

The purpose of this paper is to explore to which extent the quality of social media short text without extensions can be investigated and what are the predictors, if any, of such short text that lead to trust its content.

The paper applies a trust model to classify data collections based on metadata into four classes: Very Trusted, Trusted, Untrusted and Very Untrusted. These data are collected from the online communities, Genius and Stack Overflow. In order to evaluate short texts in terms of its trust levels, the authors have conducted two investigations: (1) A natural language processing (NLP) approach to extract relevant features (i.e. Part-of-Speech and various readability indexes). The authors report relatively good performance of the NLP study. (2) A machine learning technique in more precise, a random forest (RF) classifierusing bag-of-words model (BoW).

The investigation of the RF classifier using BoW shows promising intermediate results (on average 62% accuracy of both online communities) in short-text quality identification that leads to trust.

As social media becomes an increasingly new and attractive source of information, which is mostly provided in the form of short texts, businesses (e.g. in search engines for smart data) can filter content without having to apply complex approaches and continue to deal with information that is considered more trustworthy.

Short-text classifications with regard to a criterion (e.g. quality, readability) are usually extended by an external source or its metadata. This enhancement either changes the original text if it is an additional text from an external source, or it requires text metadata that is not always available. To this end, the originality of this study faces the challenge of investigating the quality of short text (i.e. social media text) without having to extend or modify it using external sources. This modification alters the text and distorts the results of the investigation.

This study aims to investigate the relationship between earnings quality and corporate voluntary disclosure among Malaysian listed companies. Moreover, it examines the moderating effect of the ownership structure on the relationship between earnings quality and corporate voluntary disclosure.

This study covers 300 companies listed on Bursa Malaysia. It has used strategic, financial and non-financial information to measure voluntary disclosure; earnings management, persistence and smoothness to measure earnings quality; and institutional and managerial shareholders to measure ownership structure. Hierarchical regression analysis was used to investigate if ownership structure moderates the relationship between earnings quality and corporate voluntary disclosure.

The results in this work imply that companies with high earnings quality are more likely to disclose voluntary information to help stakeholders. Furthermore, this study provides original evidence that institutional ownership and managerial ownership play a main role as moderating variables that influence management motives toward practices of voluntary disclosure and earnings quality.

Because of the limited number of empirical studies on the relationship between voluntary disclosure and earnings quality, this study fills a gap in the literature by investigating the relationship between them. In addition, a lack of research exists on the effects of ownership structure on the relationship between voluntary disclosure and the earnings quality. Therefore, this study makes an original contribution to the literature by using institutional and managerial ownership as moderating variables to investigate the effects of the ownership structure on the relationship between voluntary disclosure and earnings quality in Malaysian companies.

Several organizations decided to work remotely after the Indian Government proclaimed a state of emergency on March 24, 2020, to prevent the spread of COVID-19. Employees across all industries, particularly the Generation-Y, were stressed as a result of the COVID-19 outbreak. The purpose of this study is to fills that gap by looking at the effects of occupational stress factors (such as coworker support, work–life balance [WLB] and role expectation conflict) on Generation-Y employees in the educational sector during COVID-19.

The causes and consequences of the three occupational stresses listed above were investigated. In total, 231 surveys from workers at private and public educational institutions in India were analyzed using partial least square-structural equation modeling analysis.

The results revealed that support from coworkers greatly reduced job stress, the WLB had a positive impact on the work and personal lives, and the lack of role specification in Generation-Y employees had a negative impact on their job performance.

This study has considered the occupational stress variables among Generation-Y in the era of COVID-19, which need attention to improve the performance of the academic sector.

Aiming to resolve cross-cultural paradoxes in combining artificial intelligence (AI) with human intelligence (HI) for international humanitarian logistics, this paper aims to adopt an unorthodox Yin–Yang dialectic approach to address how AI–HI interactions can be interpreted as a sophisticated cross-cultural knowledge creation (KC) system that enables more effective decision-making for providing humanitarian relief across borders.

This paper is conceptual and pragmatic in nature, whereas its structure design follows the requirements of a real impact study.

Based on experimental information and logical reasoning, the authors first identify three critical cross-cultural challenges in AI–HI collaboration: paradoxes of building a cross-cultural KC system, paradoxes of integrative AI and HI in moral judgement and paradoxes of processing moral-related information with emotions in AI–HI collaboration. Then applying the Yin–Yang dialectic to interpret Klir’s epistemological frame (1993), the authors propose an unconventional stratified system of cross-cultural KC for understanding integrative AI–HI decision-making for humanitarian logistics across cultures.

This paper aids not only in deeply understanding complex issues stemming from human emotions and cultural cognitions in the context of cross-border humanitarian logistics, but also equips culturally-diverse stakeholders to effectively navigate these challenges and their potential ramifications. It enhances the decision-making process and optimizes the synergy between AI and HI for cross-cultural humanitarian logistics.

The originality lies in the use of a cognitive methodology of the Yin–Yang dialectic to metaphorize the dynamic genesis of integrative AI-HI KC for international humanitarian logistics. Based on system science and knowledge management, this paper applies game theory, multi-objective optimization and Markov decision process to operationalize the conceptual framework in the context of cross-cultural humanitarian logistics.

COVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in the manufacturing industry, have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore, it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains.

In this study, a new circular-SCOR model is proposed, and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method, separately.

As a result, for both methods, in the case study discussed, the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains.

It is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains, especially in manufacturing industries.

This study aims to investigate the monitoring role of ownership structure (OWS) on real earnings management (REM) practices; previous studies primarily examined the effect of OWS on accrual-based earnings management.

The sample of this study is 490 companies listed on the Malaysian Stock Exchange during the period 2013–2016 (1,960 company-year observations). The regression of a feasible generalized least square was used for data analysis. The authors use three regression models ordinary least squares, panel-corrected standard errors and Driscoll–Kraay standard errors to corroborate the findings and also examine alternative REM measures.

Analysis of the data shows that family, foreign and institutional ownership has a positive link with the quality of financial reporting and, to a large extent, is capable of alleviating REM. The findings also indicate that some form of OWS significantly affects REM, corroborating existing theories on corporate governance (CG) and the perspectives of practitioners.

The evidence concerns the significant role played by the OWS in reducing REM activities. The findings are useful in support of regulatory activities, particularly in the design of policies to regulate the OWS. The results may also provide useful insights to inform other policymakers, investors, shareholders and researchers about the active role of family, foreign and institutional investors in monitoring Malaysia's public listed companies (PLCs) to strengthen CG practices. This also leads to less REM and enhances the quality of financial reporting.

To the authors' knowledge, this work is pioneering research from a developing country, specifically from Malaysia, to investigate the manner in which all possible OWSs influence REM. More importantly, the study recommends that regulators and researchers do not envisage OWS as a holistic phenomenon.

This study aims to investigate the impact of trust in the metaverse on the Islamic banking sector, particularly in facilitating market success. Additionally, it seeks to explore the relationship between metaverse-driven brand image, product features, service quality and overall performance in the market.

Data were collected from 187 participants in Jordan, with the SmartPLS software used to test the hypotheses.

The findings reveal a significant impact of metaverse-enhanced brand image, product features and service quality on Islamic banking market performance. Furthermore, customer trust in the metaverse plays a significant role in shaping the relationship between product features, service quality and Islamic banking market performance.

The study’s practical implications still suggest the need for a more holistic metaverse-driven approach. Investing in service quality initiatives alone may not adequately build and sustain customer trust in the metaverse. Instead, transparent communication on ethical practices in the metaverse is required to reinforce trust and magnify the positive influence of superior service quality in the metaverse.

The purpose of this paper is to investigate how corporate cash holdings changes across firm life cycle and how firms undergo heterogeneous dynamic cash adjustment as they advance from one stage to the next stage.

This study uses an extensive data set of 2,994 Chinese A-listed firms. The authors use generalized method of moments (GMM) and Fisher Panel unit root testing to investigate the targeting behavior of Chinese firms.

The uni-variate investigation reveals that firms in the growth stage exhibits the highest cash levels and firms in the decline stage report the lowest cash levels. As growth firms have high investment needs, they may require raising external capital to meet investment needs. To avoid the costly external financing, firms in growth stage tend to hold more cash. The GMM estimation reveals that along all the phases of firm life cycle there are evidences of trade-off behavior of corporate cash holdings. The authors report that adjustment rate increases as firms enters into the growth stage.

The findings provide both theoretical and practical insight to align cash policies with the available strategic choices along firm life cycle in an emerging market characterized by market imperfections.

The study is unique from the context that it is applying robust methodology to one of rarely investigated area in corporate cash policy. The peculiar Chinese study setting characterized by higher information asymmetry, high cost of external financing and heterogeneous access to financing sources provide theoretical and empirical underpinnings to investigate and gain insight about how corporate cash policy can be aligned with strategic choices available across different stages of life cycle.