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This paper aims to examine the concept of standardization beyond its traditional use in generating and implementing standards and good practice guidelines (S&GPG) by looking at existing and emerging trends.

This paper utilizes two primary approaches to categorizing S&GPG for better comprehension: categorization based on provenance as well as based on subject matter.

A significant concern related to categorizing S&GPG based on provenance or subject is the constant proliferation of standards being developed and introduced every year. This rapid growth in standards requires frequent re-categorization to keep up with the dynamic nature of this field. To tackle this problem, this paper explores emerging concepts such as ontological representation and frameworks that offer archives and records management (ARM) professionals.

Standardization refers to establishing uniform rules through mutual agreement to ensure consistency. The study of standardization goes beyond the development of individual S&GPG, encompassing their practical application in work settings. Categorizing standards alone may not fully capture their actual use. However, abstraction mechanisms like ontological representations, models and frameworks can demonstrate how these standards have been leveraged. This paper provides illustrative examples rather than an exhaustive list to showcase how these mechanisms have been applied in research projects or as practical tools.

This paper explores the emerging topic of standardization from the perspective of ontological representations and models or frameworks. In addition, it also contributes to the discussion of the 2022 version of ARMA International’s Information Governance Implementation Model and the 2020 version of the World Bank Group's Records Management Roadmap, providing unique insights into these topics.

Despite agreement on the importance of adopting governance structures for developing competitive advantage, we still know little about why or how governance mechanisms are adopted in the first place. We also acknowledge that family businesses with formal governance mechanisms in place still resort to informal means to make decisions, and we lack knowledge about why certain governance mechanisms are sometimes, but not always, effective and functional. Given these research gaps, and drawing on institutional theory, we aim to explore: How are governance structures adopted and developed in family firms? Once adopted, how do family businesses perceive these governance structures?

Using Mokken Scale Analysis, a method suitable to uncover patterns/sequences of adoption/acquisition over time, we analyze a dataset of 1,488 Spanish family firms to explore if there is a specific pattern in the implementation of governance structures. We complement the analysis with descriptive data about perceived usefulness of such structures.

Our findings highlight two important issues. Family businesses follow a specific process implementing first business governance (board of directors, then executive committee), followed by family governance (family council then family constitution). We suggest they do so in response to institutional pressures, given the exposure they have to business practices, and their need to appear legitimate. Despite formal adoption of governance structures, family businesses do not necessarily consider them useful. We suggest that their perception about the usefulness of the implemented governance structures may lead to their ceremonial adoption, resulting in a gap between the implementation and functionality of such structures.

Our article contributes to the family business literature by bringing novel insights about implementation of governance structures. We take a step back to explain why these governance mechanisms were adopted in the first place. Using institutional theory we enrich governance and family business literatures, by offering a lens that explains why family businesses follow a specific process in adopting governance structures. We also offer a plausible explanation as to why governance structures are ineffective in achieving their theorized role in the context of family businesses, based on the family's perception of the unusefulness of such structures, and the concept of ceremonial adoption.

There is no single recipe that can serve the multiple needs of different family businesses. This indicates that family businesses may need diverse levels of development and order when setting up their governance structures. Accordingly, this study constitutes an important point of demarcation for practitioners interested in examining the effectiveness of governance structures in family firms. We show that an important pre-requisite for examining the effectiveness of governance structures is to start by investigating whether these structures are actually being used or are only adopted ceremonially.

Our paper expands current knowledge on governance in family firms by taking a step back hinting at why are governance structures adopted in the first place. Focusing on how governance is implemented in terms of sequence is novel and relevant for researcher and practitioners to understand how this process unfolds. Our study uses institutional theory, which is a strong theory to support the results. Our paper also uses a novel method to study governance structures in family firms.

Business rescue, as a mechanism to aid financially distressed companies in South Africa, has received considerable academic and practical recognition. However, the business rescue plan is an overlooked and, perhaps, underdeveloped aspect of the regime. For stakeholders, this is the ultimate decision-making document. Creditors are the most influential stakeholders in business rescue proceedings owing to their voting rights. For creditors to make informed decisions and exercise their votes meaningfully, the business rescue plan should be transparent and adequately disclose relevant and reliable information. This study aims to identify creditors’ primary information needs to enhance the sufficiency and decision-usefulness of business rescue plans, not only to entice the vote of creditors but to enforce accountability from practitioners.

Using a qualitative research design, semi-structured interviews were conducted with 14 executives from 10 South African financial institutions.

The findings reveal that comprehensive disclosure of financial, commercial and legal information in business rescue plans was a critical antecedent for stakeholder decision-making. Additionally, leadership and social impact information were influential determinants. This study advances academic knowledge and, for practitioners, adds value to the development of business rescue plans. This can enhance creditors' confidence in supporting the rescue effort and approving the plan.

This study advances academic knowledge and, for practitioners, adds value to the development of business rescue plans. This can enhance creditors' confidence in supporting the rescue effort and approving the plan.

The originality of this article lies in its investigation of how creditors assess the information in BR plans as a precursor to supporting the company’s reorganisation in a creditor-friendly business rescue system such as South Africa. This study provides novel insights into the decision-making process, particularly how creditors assess BR plans, address information asymmetry and vote on the plan.

Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can potentially diminish rates of adolescent pregnancy, given that educational attainment stands as the foremost risk factor influencing sexual initiation, the use of contraceptive methods during initial sexual encounters and fertility. The aim of this paper is to analyze the impact of the implementation of the public educational policy introducing full-time schools (FTS) for high schools in the state of Ceará, Brazil, on early pregnancy rates.

Using the difference-in-differences method with multiple time periods, we measured the average effect of this staggered treatment on the treated municipalities.

The main result indicates a reduction of 0.849 percentage points in the teenage pregnancy rate. Concerning dynamic effects, the establishment of FTS in treated municipalities results in a 1.183–1.953 percentage point decrease in teenage pregnancy rates, depending on the timing of exposure. We explored heterogeneous effects within socioeconomically vulnerable municipalities, yet discerned no impact on this group. Rigorous tests confirm the robustness of the results.

This paper aims to contribute to: (1) the consolidation of research on the subject, given the absence of such research in Brazil to the best of our knowledge; (2) the advancement and analysis of evidence-based public policy and (3) the utilization of novel longitudinal data and methodology to evaluate adolescent pregnancy rates.

During the COVID-19 pandemic, Local Educational Management Units (UGELs), the key government stakeholders in the provision of education services in Peru, implemented responsive interventions. This paper analyses the relationship between UGEL organisational resilience and their responses during this period.

A survey was conducted to measure UGEL management practices, with 251 valid responses from directors and managers. Based on organisational resilience theory, 67 questions were grouped into 13 factors and 3 components: (1) leadership and organisational culture, (2) preparation for change, and (3) networks building on the Organisational Resilience Index (ORI). These factors correlated with the number of interventions and the impact of those interventions implemented by UGELs.

The findings indicated that of all ORI components, leadership and organisational culture ranked the highest. Moreover, the ORI is positively associated with the number of interventions and the perceived impact produced by those interventions. Interestingly, it was found that when the gender variable is included in the correlation between the ORI and the number of interventions, women leading UGELs display a higher number of interventions than their male counterparts; and the coefficient increases even more when women lead a UGEL in a more challenging context (i.e., when the UGEL is located in a low-income area and operates under scarce resources).

This is the first study in Peru which analyses organisational resilience in the education sector, specifically about UGELs during the COVID-19 pandemic. It may help set priorities for institutional strengthening initiatives aimed at improving organisational resilience, which is particularly important in such uncertain and changing contexts.

Social networks (SNs) have recently evolved from a means of connecting people to becoming a tool for social engineering, radicalization, dissemination of propaganda and recruitment of terrorists. It is no secret that the majority of the Islamic State in Iraq and Syria (ISIS) members are Arabic speakers, and even the non-Arabs adopt Arabic nicknames. However, the majority of the literature researching the subject deals with non-Arabic languages. Moreover, the features involved in identifying radical Islamic content are shallow and the search or classification terms are common in daily chatter among people of the region. The authors aim at distinguishing normal conversation, influenced by the role religion plays in daily life, from terror-related content.

This article presents the authors' experience and the results of collecting, analyzing and classifying Twitter data from affiliated members of ISIS, as well as sympathizers. The authors used artificial intelligence (AI) and machine learning classification algorithms to categorize the tweets, as terror-related, generic religious, and unrelated.

The authors report the classification accuracy of the K-nearest neighbor (KNN), Bernoulli Naive Bayes (BNN) and support vector machine (SVM) [one-against-all (OAA) and all-against-all (AAA)] algorithms. The authors achieved a high classification F1 score of 83\%. The work in this paper will hopefully aid more accurate classification of radical content.

In this paper, the authors have collected and analyzed thousands of tweets advocating and promoting ISIS. The authors have identified many common markers and keywords characteristic of ISIS rhetoric. Moreover, the authors have applied text processing and AI machine learning techniques to classify the tweets into one of three categories: terror-related, non-terror political chatter and news and unrelated data-polluting tweets.