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The purpose of this research is to investigate how different accountability practices might be observed in the annual reports of non-government organisations (NGOs) in Bangladesh. The study further aims to understand whether such accountability disclosures support NGO legitimacy in Bangladesh and if so, in what form.

To fulfil this objective, a content analysis was conducted on the annual reports of 24 selected leading NGOs operating in Bangladesh. The data were then analysed through the not-for-profit accountability framework of Dhanani and Connolly (2012). Theoretical constructs of legitimacy were further mobilised to corroborate the evidence.

It was found that NGOs operating in Bangladesh discharged all four types of accountability, i.e., strategic, fiduciary, financial and procedural (Dhanani and Connolly, 2012) through annual reports. The findings further suggested that carrying out these accountabilities supported the legitimation process of NGOs. Moreover, we found that NGOs took care of the needs of both primary and secondary stakeholders although they widely used self-laudatory positively charged words to disclose information about their accountabilities.

The study contributes to the limited accounting research on the public disclosures of NGOs and not-for-profit firms particularly in emerging economy settings. Also, we contribute to the limited research on the accountability-legitimacy link of NGOs evident in public disclosures like annual reports.

The purpose of this study is to present an in-depth examination of stakeholder engagement processes in non-governmental organisations (NGOs) from the perspective of NGO managers to enhance accountability and the effectiveness with which aid services are delivered. Specifically, demand-side (downward) accountability and the implications of an accountability system that is predominantly supply-side (upward) focused are explored.

This study draws on evidence gathered from 25 in-depth interviews with representatives of leading NGOs in Nigeria to explore and uncover the nature of stakeholder engagement and accountability processes in their respective organisations. This study shows prospects for entrenching organisational reform that balances power and influence that benefits the less economically powerful demand side of the stakeholders. A relevant aspect of stakeholder theory was used to frame the analysis.

The study reveals an overlay of a blanket engagement system and a seeming reluctance of NGOs to disclose critical information to the demand-side stakeholders (DSS), and suggests ways to meet sustainability demands and address the militating concerns. A perceived lack of understanding and prospects or outcomes of demand-side accountability are central to this; however, engagement outcomes that account for impact rather than output are explored and reported. The findings suggest that proper accountability involves adequate stakeholder engagement which is a prerequisite and paramount for sustainability.

This study primarily delineates NGO managers’ views on NGO engagement and accountability dynamics. Future research may explore the perspectives of downward stakeholders themselves. The study highlights the concern for NGOs to maintain a defined stakeholder engagement process that resists external forces that may impact on their operations and derail their mission, resulting in duplication of services.

The study shows the implications of donors’ influence on accountability practices which can be improved by re-structuring supply-side stakeholders to significantly include DSS accountability requirements in the key performance indicators of NGOs in developing countries. The authors present a nuanced perspective to aid delivery and access that ensures improved services and more effective, impactful and sustainable aid which is of practical relevance to NGOs and their accountability mechanism.

This study deepens the understanding of the dynamics of stakeholder engagement and accountability processes and shows that the most effective way to deploy aid funds to meet sustainability goals is to draw on the experiences and local knowledge of the DSS. This would require an effective and results-driven dialogue among all the stakeholders involved. The proposed engagement and management framework contribute to theory and practice by fostering multi-stakeholder cooperation, DSS accountability and the advancement of sustainable development

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

The paper aims to investigate the dynamics of individuals' multiple commitments in the internship context by answering two questions: How do interns' commitment to different stakeholders change over time? And what are the reasons behind these changes?

A qualitative longitudinal study was conducted of a hundred and three interviews with twenty interns in three professional service firms in the UK. The data were gathered via semi-structured interviews that took place on five occasions during the whole internship.

Individuals' decision to maintain or change their commitment depended on their motive to gain long-term benefits (future employment) or short-term benefits (completing an assignment). Therefore, they experienced different types of commitment dynamics, which were influenced by their intention to commit to the organization in the future.

This offers significant implications for attracting and employing interns, which directly affects talent employment. It also contributes to the contemporary work context, as the rise of temporary and cross-boundary settings would increase the complexity and dynamics of commitment.

Despite the predominant assumption that considers commitment as a stable bond, this research is one of the first to investigate the dynamics of multiple commitments. This contributes to the commitment theory by identifying the different types of commitment dynamics and the impact of individuals' intention to commit on the (in)stability of their commitment, which is absent from the existing literature.

Most research has investigated the fear of missing out (FOMO) in the context of online activities, often associated with negative personal outcomes such as fatigue and stress. However, given the increased desire to be informed and included associated with FOMO, organizations that can effectively meet these needs may develop or strengthen social and structural bonds, thereby turning short-term customers with FOMO into lifelong patrons. This study aims to examine the relationship between FOMO and favorable organizational outcomes as mediated by several constructs associated with the desire for information and inclusion.

This research was conducted within the higher education sector of the service industry. FOMO served as the IV. The mediators represented context-specific aspects of campus involvement and inclusion. Organizational outcomes related to the long-term services relationship served as the DVs. The sample consisted of 435 students recruited from research pools at two southern universities in the USA. Exploratory factor analysis, OLS regression and the Hayes–Macro were used to examine the data.

The results demonstrate that FOMO is positively associated with students’ desires for information and inclusion (informal peer interaction, campus involvement, informal faculty interaction, campus information media use and a preference for in-person course scheduling), which are associated with the desirable university outcomes of satisfaction, connection and alumni donation/activity intentions.

If a university fosters unstructured time spent with faculty and peers, and promotes campus information media involvement, students with higher levels of FOMO are more likely to be satisfied, feel connected to the university and report intentions to donate time and money as alumni.

Prior research on FOMO is generally focused on internet and social media use; this study takes a broader perspective and identifies the effect of FOMO on a desire for information and inclusion within a novel context (a service environment). It also associates FOMO with favorable long-term service relationship outcomes that fortify social and structural bonds.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.

Conceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.

The predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.

Better understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.

因此,就了解經濟週期和經濟發展而言,流動資金是一個極其重要的概念。本研究擬在安全資產的價格預測方面取得進步。安全資產代表了經濟的實際情況,特別是美國的十年期國債。

流動資金的定義上面已說明了; 為進一步了解經濟波動,本研究擬對流動資金代表性變量的預測能力進行評估。

研究使用作為流動資金代表的概念變項去規劃預測。各機器學習模型的結果會作比較,這會帶來對流動資金變量的預測值的深思,而深思的目的是確定其選擇。

只要在私營部門內流動資金的數據比公營部門的流動資金數據、在預測經濟波動方面貢獻更大時,我們發現、模型的預測能力也會依賴流動資金的來源而存在差異。國際流動資金被視為一個晦澀的概念,而它的定義的標準化,或許應是未來學術研究的焦點。當應用最先進的機器學習模型時,標桿分析法的步驟也施行了。

若我們對有關的變量加深認識,我們就可更深入地理解金融市場的運作。流動資金,雖是金融市場中一個極其重要的變量,但在現存的學術文獻裏,不但沒有明確的定義,而且也沒有被標準化; 就此而言,未來的研究或許可在這方面作進一步的探討。因此,本研究為富有新穎思維的應用研究,研究使用了現代數據科學技術,這可為探討金融市場提供一個全新的視角。

This paper aims to investigate place marketing and branding at the micro-place scale through the case study of St Christopher’s Place in London (UK). This study illustrates the distinctive differences of micro-place marketing, in comparison to city and country levels.

An exploratory case study was conducted through a sequential mixed methods approach involving direct observation, semi-structured interviews, questionnaires and social media analysis. Analysis of data was performed by using thematic analysis and triangulation of quantitative measures collected through the questionnaire and social media analysis.

Analysis of data illustrated noticeable differences of place management at the micro-place level compared to city or country scale of place marketing and branding. The function of emotional marketing leading to value co-creation is more effective at this level, establishing close and personal ties between occupiers and customers. Yet, measurement of micro-place marketing and branding value creation is difficult to achieve.

This study draws attention to the unique value and benefits of place branding at smaller spatial scales. Findings contribute to the place micro-brand concept by adding knowledge of micro-places through place management activities comparing them with city and country scales, and emotional marketing value co-creation practices, including challenges relating to measurement.

The world is on the verge of entering the deglobalization age, and industrialized economies have ushered it in. However, there is still a scarcity of comprehensive and rigorous studies in this field. This research has tried to analyze the evolution and characteristics of deglobalization research.

The authors have employed bibliometric analysis for examining the existing evidence on accelerating deglobalization thinking based on a thorough analysis of articles published during a roughly 25-year span between 1996 and 2022. This study has used the TISM-P technique to study the relationship among the factors accelerating deglobalization thinking. This research reviews the articles on several dimensions of deglobalization using the “what”, “why”, “how”, “who”, “when” and “where” approaches.

The authors specify the critical factors, policy reforms, approaches and observed characteristics explored in this developing research area.

The authors have analyzed the factors accountable for rising deglobalization thinking and also suggested strategic recommendations based on the findings to minimize the adverse impact of globalization.

Although there is a wealth of literature on globalization, very little study has been done in the field of deglobalization. This is the first substantive review being done in the deglobalization domain. The contemporary research has used the bibliometric approach and the “5W and 1 H” framework to gain a comprehensive understanding of the changing paradigm.

This paper aims to fabricate a polymer-based polyethylene glycol (PEG) coating with acrylic resin as a binder that can show antiviral activity against the feline coronavirus (FCov) on the glass substrate.

The PEG/acrylic coating systems of different weight percentages were coated on the glass substrates using the spray-coating method and cured at room temperature for 24 h.

The coating system containing 20 Wt.% of PEG exhibits the highest antiviral activities as high as 99.9% against FCov compared with other samples.

Findings will be useful in the development of antiviral coating for PPE fabrics by using the simple synthesis method.

Application of PEG as an antiviral agent in the antiviral coating system with high antiviral activities about 99.9%.