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Research on green certificate rankings in the MENA region primarily focuses on building scale, relying on the certified project count. This assessment approach overlooks the spatial factor, failing to capture their influence on the urban built environment, thus potentially undermining other efforts not reflected by the project count. This research aims to rank countries in the Middle East and Northern Africa (MENA) region based on their ongoing efforts regarding green neighbourhood certification.

This study employs a three-phase methodology to rank MENA countries' adoption of green neighbourhood certification systems: content analysis, multicriteria analysis (MCA) using the analytical hierarchy process (AHP) and spatial analysis.

Based on the content analysis, four major performance indicators were identified and the conventional ranking using projects count was presented. Using AHP, the MCA could rank the countries in the region according to their unique performance indicators score, clarifying the differences between conventional and AHP-based rankings. Finally, the spatial analysis phase uncovers shortcomings in the traditional ranking method, revealing inaccuracies and misrepresentations for several countries.

The study presents an innovative ranking methodology to monitor the green neighbourhood actions of countries in future development and establish a pioneering framework to evaluate the impact of green certifications within the region.

Construction projects commonly encounter complicated delay problems. Over the past few decades, numerous delay analysis methods (DAMs) have been developed. There is no consensus on whether existing DAMs effectively resolve delays, particularly in the case of complex concurrent delays. Thus, the primary objective of this study is to undertake a comprehensive and systematic literature review on concurrent delays, aiming to answer the following research question: Do existing delay analysis techniques deal with concurrent delays well?

This study conducts a comprehensive review of concurrent delays by both bibliometric and systematic analysis of research publications published between 1982 and 2022 in the Web of Science (WoS) and Scopus databases. For quantitative analysis, a bibliometric mapping tool, the VOSviewer, was employed to analyze 68 selected publications to explore the co-occurrence of keywords, co-authorship and direct citation. Additionally, we conducted a qualitative analysis to answer the targeted research question, identify academic knowledge gaps and explore potential research directions for solving the theoretical and practical problems of concurrent delays.

Concurrent delays are a critical aspect of delay claims. Despite DAMs developed by a limited number of research teams to tackle issues like concurrence, float consumption and the critical path in concurrent delay resolution, practitioners continue to face significant challenges. This study has successfully identified knowledge gaps in defining, identifying, analyzing and allocating liability for concurrent delays while offering promising directions for further research. These findings reveal the incompleteness of available DAMs for solving concurrent delays.

The outcomes of this study are highly beneficial for practitioners and researchers. For practitioners, the discussions on the resolution process of concurrent delays in terms of identification, analysis and apportionment enable them to proactively address concurrent delays and lay the groundwork for preventing and resolving such issues in their construction projects. For researchers, five research directions, including advanced DAMs capable of solving concurrent delays, are proposed for reference.

Existing research on DAMs lacks comprehensive coverage of concurrent delays. Through a scientometric review, it is evident that current DAMs do not deal with concurrent delays well. This review identifies critical knowledge gaps and offers insights into potential directions for future research.

Behaviours occur across complex, dynamic timelines. Research methods to analyse these complex timelines have repeatedly used behaviour sequence analysis (BSA) as a primary method. Traditional BSA outputs, however, are limited in that they do not show how prevalent a behaviour sequence is throughout a sample or group. Until now, how many people in a sample showed the sequence was not analysed and reported. This paper aims to provide a new metric to calculate prevalence scores in BSA data sets.

Open access recorded responses including nonverbal communication of deceptive and truthful individuals were analysed initially with a standard BSA approach and then the prevalence scores of transitions were calculated.

Prevalence scores offered new insights into the distribution of sequences across groups. The prevalence score showed differences in which transitions were seen across the truthful and guilty samples. This offers new approaches to analysing nonverbal communication.

This is the first paper to provide a prevalence score for BSA research and show how it can be used in applied research. The current prevalence score metric is provided and suggested for all future research into sequences.

Sentiment analysis is a text analysis method that is developed for systematically detecting, identifying, or extracting the emotional intent of words to infer if the text expresses a positive or negative tone. Although this novel method has opened an exciting new avenue for organizational research – mainly due to the abundantly available text data in organizations and the well-developed sentiment analysis techniques, it has also posed a serious challenge to many organizational researchers. This chapter aims to introduce the sentiment analysis method in the text mining area to the organizational research community. In this chapter, the authors first briefly discuss the central role of sentiment in organizational research and then introduce the traditional and modern approaches to sentiment analysis. The authors further delineate research paradigms for text analysis research, advocating the iterative research paradigm (cf., inductive and deductive research paradigms) that is more suitable for text mining research, and also introduce the analytical procedures for sentiment analysis with three stages – discovery, measurement, and inference. More importantly, the authors highlight both the dictionary-based and machine learning (ML) approaches in the measurement stage, with special coverage on deep learning and word embedding techniques as the latest breakthroughs in sentiment and text analyses. Lastly, the authors provide two illustrative examples to demonstrate the applications of sentiment analysis in organizational research. It is the authors’ hope that this chapter – by providing these practical guidelines – will help facilitate more applications of this novel method in organizational research in the future.

This paper aims to review empirical research on the relationship between institutional ownership (IO) and board governance (85 studies).

Based on agency and upper echelons theory, the heterogeneous monitoring function of specific types and the nature of institutional investors on board composition, compensation and chief executive officer (CEO) characteristics will be focused.

The author found that most studies have referred to archival studies, analyzed the impact of board governance on IO, focused on CEO characteristics, neglected IO heterogeneity and advanced regression models to address endogeneity concerns. In line with the theoretical framework, the relationship between total IO and board governance is heterogeneous. However, specific types such as foreign, dedicated and pressure-resistant institutions represent active monitoring tools and push for increased board governance.

The author provided useful recommendations for future research from a content and methodological perspective, e.g. the need for analyzing the impact of IO on sustainable board governance and other characteristics of top management team members, e.g. the chief financial officer.

As many regulatory bodies implemented regulations to promote shareholder rights and board governance, this literature review highlights the connections of both corporate governance mechanisms. Managers should conduct a careful and timely investor analysis and change the composition and compensation of the board of directors in line with institutional investors’ preferences.

This analysis makes useful contributions to prior research by focusing on IO and board governance, whereas the author structured the heterogeneous variables and results within the structured literature review. The authors guides researchers, regulatory bodies and business practice in this corporate governance topic.

This paper aims to examine the mismatch between multidimensional deprivation and monetary poverty in identifying the poor in Egypt and investigates their determinants empirically.

The paper uses the Alkire-Foster multidimensional poverty measurement method using data from Egypt’s 2017/2018 Household Income, Expenditure and Consumption Survey (HIECS 2017/2018). Using a logistic regression model, the paper assesses the empirical relationship between multidimensional and monetary poverty and their determinants at the aggregate level and by dimension.

The paper demonstrates a significant mismatch between multidimensional and monetary poverty measures, underscoring their complementary nature. Statistics indicate that both measures overlap in classifying 35.81% of Egyptians, whereas monetary poverty ignores 63.12% of multidimensionally poor in at least one dimension. Regression estimates show a significant moderate negative association between expenditure per capita and multidimensional poverty and its dimensions. Moreover, they show that household head’s gender, age, education attainment, marital status, job proficiency, household size and location affect poverty mismatch and match in Egypt.

This paper offers Egyptian policymakers the multidimensional poverty index that enables more efficient designing and targeting of poverty alleviation programs and assessing current poverty alleviation programs to modify them if needed.

To the best of the authors’ knowledge, this study is the first to examine the mismatch between both poverty measures in Egypt, using the recent full data set of HIECS 2017/2018. This paper confirms that depending only on monetary measures can send inaccurate insights for crafting effective social policies. Also, it offers policymakers a comprehensive insight into the country’s poverty landscape, which enable more efficient design, targeting of poverty alleviation programs and monitoring their effectiveness.

This study aims to present a bibliometric overview of the academic research on export performance (EP) in the business and management areas.

A bibliometric overview of 1,463 papers from 1968 to 2021, including performance analysis, science mapping analysis and graphical mapping, was conducted using the Scopus database. SciMAT software was used for thematic analysis and conceptual evolution mapping of the EP domain, and VOSviewer software was used for graphical visualization.

This study shows that EP research experienced spectacular growth, especially between 1998 and 2003, and the interest in this field continues to increase. Also, the USA and the UK appear to be the absolute leaders in EP research, with the best indicators of productivity and influence in all dimensions analyzed. The findings from the analysis through SciMAT indicate that “capabilities” and “R&D” are the main Motor themes that have contributed the most to the EP literature, whereas “global value chain” and “start-up” are emerging themes as new areas of interest.

This study develops a baseline for representing certain and exhaustive insights in the EP field and specifies trends over a period. Using a single database and excluding book chapters/conference papers are limitations of this study.

EP is a research field that has gained wide acceptance in the academic community and international marketing literature. To the best of the authors’ knowledge, no bibliometric overview has analyzed the EP literature. This study presents the first systematic quantitative analysis of academic research on EP in the business and management areas.

This study aims to investigate how phishers apply persuasion principles and construct deceptive URLs in mobile instant messaging (MIM) phishing.

In total, 67 examples of real-world MIM phishing attacks were collected from various online sources. Each example was coded using established guidelines from the literature to identify the persuasion principles, and the URL construction techniques employed.

The principles of social proof, liking and authority were the most widely used in MIM phishing, followed by scarcity and reciprocity. Most phishing examples use three persuasion principles, often a combination of authority, liking and social proof. In contrast to email phishing but similar to vishing, the social proof principle was the most commonly used in MIM phishing. Phishers implement the social proof principle in different ways, most commonly by claiming that other users have already acted (e.g. crafting messages that indicate the sender has already benefited from the scam). In contrast to email, retail and fintech companies are the most commonly targeted in MIM phishing. Furthermore, phishers created deceptive URLs using multiple URL obfuscation techniques, often using spoofed domains, to make the URL complex by adding random characters and using homoglyphs.

The insights from this study provide a theoretical foundation for future research on the psychological aspects of phishing in MIM apps. The study provides recommendations that software developers should consider when developing automated anti-phishing solutions for MIM apps and proposes a set of MIM phishing awareness training tips.

The purpose of this study is to assess the value of altmetrics or other indicators, showcasing the impact of academic output, which is seen too often correlated with the citation count.

This study considered three reputed journals of Library and Information Science (LIS) published by Elsevier. A total of 1,164 articles were found in these journals from 2016 to 2020 and the relationships between altmetric attention scores (AAS) and citations were examined. The analysis was extended to compare the grouped data set based on percentile ranks of AAS like top 50%, top 25%, top 10% and top 1%.

Using Spearman correlation analysis, the findings reveal a positive correlation between AAS and citations with different significant levels for all articles, and articles with AAS, as well as for normalized AAS in the top 50%, top 25%, top 10% and top 1% data set. For the three journals International Journal of Information Management (IJIM), Journal of Informetrics (JIF) and Library and Information Science Research (LISR), a significant positive correlation is observed across all data sets. But an unexpected result was observed: in the case of the top 50% of articles for the IJIM and JIF showed no significant correlation but the LISR journal showed a positive correlation for the whole data set. This journal though has fewer articles in comparison to the other two.

A source item that is highly cited may not be having high social media attention as reflected in the findings. This demarcates AAS with citations implying various factors on which these measurements are dependent. The study distinguishes these metrics lucidly. There is not a single guideline or uniformity in assessing the correlation found. But the problem is that the interpretation of the correlation strength affects the conclusion of the study. Moreover, this study will be a role model as a draft for librarians to select relevant journals for their libraries and will facilitate authors in the choice of the publication outlets for their papers, particularly concerning the journals that have both visibility and research impact.

The study reported devising a comprehensive tool to validate AAS as a measure of scholarly impact to include appropriate social media sources and verify its relationship with other metrics. To the best of the authors’ knowledge, this paper is the first attempt to discover the correlation between AAS and citations for the highly impactful LIS journal published by Elsevier. The empirical evidence lies in the citation and altmetric data extracted from the dimension database.