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This study examines the association between corporate tax avoidance and the cost of debt (COD). It also investigates the moderating effect of integrated report (IR) assurance on tax avoidance/COD relationship.

Based on a sample of 76 South African companies listed on the Johannesburg Stock Exchange (JSE) from 2010 to 2020, the authors built and estimated regression models using the feasible generalized least squares (FGLS) method. The authors significantly mitigated the endogeneity concerns using propensity score matching (PSM), difference-in-differences (DID) analysis and fixed effects regression.

The authors found that tax-avoiding firms pay higher costs of debt due to information asymmetries and agency problems. Bankers systematically reflect the increase in tax avoidance by adjusting the COD upward. However, results show that the assured IR disclosure mitigates these problems, which decreases the COD for tax avoidance strategies adopters. Using a quasi-natural experiment, well-grounded evidence was provided showing that the decrease in the COD for debtors who engage in tax avoidance practices is attributed to the availability of an assured IR.

This study provides plausible evidence in favor of the role that an assured IR can play in capital allocation decisions. Consequently, it is likely to push policymakers in South Africa and other countries to set standards for IR assurance.

This is the first study that investigates and validates the role of IR assurance in solving the controversy about the “tax saving effect” vs. “risk exposure effect” that bankers face while identifying debtors with successful (non-risky/cash-saving) tax avoidance practices and those with non-successful (risky) ones.

The purpose of the study is to examine the impact of corporate reputation (hereafter CR) and the degree of economic development on firms’ cost of capital remains unresolved. This study addresses these issues.

Using a global sample across 20 countries, the study investigates the discrete and joint effects of CR and jurisdictional economic development on the cost of equity (COE) and cost of debt (COD) capital. The analysis encompasses a dual data set, comprising 1,308 observations for COE and 1,223 observations for COD, allowing for a comprehensive exploration of these dynamics.

The findings indicate that CR leads to a reduction in the cost of capital for reputable firms. Nevertheless, the extent of this decrease varies per type of capital and firm’s reputation level and is contingent upon the economic development level within the firm’s jurisdiction. Particularly noteworthy is the moderating effect of economic development on CR, which shows that COE capital tends to be lower for reputable firms operating in economically developed jurisdictions. Albeit, this is not the case for COD capital for reputable firms in similarly developed jurisdictions.

This study illustrates that effective CR management, aimed at reducing the cost of capital, necessitates a combination of the firm’s unique competitive advantage and the economic development context of its jurisdiction to truly achieve its intended goal.

To the best of the authors’ knowledge, this is the first global study to explore the impact of CR on both COE and COD capital. Furthermore, this study is primarily towards understanding the moderating role of economic development in the relationship between CR and cost of capital.

This paper aims to study the application of high-tolerance and flexible indigenous bacteria and fungi, along with the co-metabolism in recycled paper and cardboard mill (RPCM) wastewater treatment (WWT).

The molecular characterization of isolated indigenous bacteria and fungi was performed by 16S rRNA and 18S rRNA gene sequencing, respectively. Glucose was used as a cometabolic substrate to enhance the bioremediation process.

The highest removal efficiency was achieved for both chemical oxygen demand (COD) and color [78% COD and 45% color removal by Pseudomonas aeruginosa RW-2 (MZ603673), as well as approximately 70% COD and 48% color removal by Geotrichum candidum RW-4 (ON024394)]. The corresponding percentages were higher in comparison with the efficiency obtained from the oxidation ditch unit in the full-scale RPCM WWT plant.

Indigenous P. aeruginosa RW-2 and G. candidum RW-4 demonstrated effective capability in RPCM WWT despite the highly toxic and low biodegradable nature, especially with the assistance of glucose.

The purpose of this study is to examine how lenders alter their behavior when faced with real earnings management.

This study uses the incremental R-square approach as in Kim and Kross (2005) to examine how much lenders rely on income statement and balance sheet ratios as the degree of real earnings management increases.

As real earnings management affects mostly the income statement, the authors find that lenders rely less on income statement ratios in making credit decisions in the presence of real earnings management. The authors also find that lenders do not alter their reliance on balance sheet ratios when faced with real earnings management.

This paper is the first to study how lenders alter their reliance on financial statements in making credit decisions in the presence of real earnings management. The findings of this paper could help the regulators set standards to improve the usefulness of financial statements. The findings of this paper could also help practitioners (borrowers and lenders) understand how real earnings management affects credit decisions.

This paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.

The study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.

The use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.

Integrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.

This paper aims to evaluate the performance of the Mashhad No. 5 wastewater treatment plant (WWTP) using a combination of data mining (regression) algorithms and artificial neural networks.

In this research, the performance of WWTP located in Mashhad, Iran, has been evaluated using two data mining models, neural network and regression model.

The proposed model has the potential of implementing in other WWTPs in Iran or other countries.

The authors would also like to thank Mashhad No.5 WWTP for data access.

Christmas is the most consumed event of the year, always full of traditions, namely family ones, which are very significant. In this way, it is intended to find out the importance of traditions at Christmas time and analyze their implications for family businesses.

The study is quantitative in nature, based on a questionnaire survey carried out with 551 Portuguese individuals, over 18 years of age, where different issues related to Christmas traditions and family are addressed.

The results demonstrate that the Christmas traditions scale is made up of four factors: family traditions on Christmas Eve, aspects related to the Christmas spirit, changes in Christmas traditions with the COVID-19 pandemic and traditions of participating in events with family at Christmas. Cod and octopus dishes are the most popular dishes on Christmas Eve. In relation to sweets/desserts, king cake, rabanadas, vermicelli, children's bread and sponge cake are the most common on Christmas Eve.

The study helps to understand Portuguese Christmas traditions, providing knowledge that allows defining strategies for family businesses, improving the experience and relationship with consumers at a special time of year. It is hoped that the trends in Christmas traditions in this study will contribute to unveiling the Christmas spirit, also serve as a marketing image and create curiosity and motivation on the part of other cultures to visit Portugal during this festive season, in order to experience Christmas traditions.

In the current chapter, we discuss the shape and contours of the field of probation in Romania as they appear in scientific literature and mass media, focusing on the concerns academics and professionals have voiced about Romanian probation. We analyse the timeframe from 2014 to 2021, after the introduction of the country’s New Penal Code (NPC). We structure our argument as follows. The chapter begins with a short incursion into the historiography of probation as a field in Romania. The focus, however, is on the adoption of a NPC in 2014, as this was a significant moment that led to changes for both probation workers and probationers. While we present the first 25 years since probation was instituted in Romania in 1997 as a period of experiments, trials and errors, we aim to highlight the development and consolidation that occurred in the period after 2014 (see Durnescu 2008, 2015; Preda, 2015a, 2017; Sandu, 2016). The NPC was intended to bring forward a reconfiguration of the probation system in Romania (Preda, 2015b). Beyond the promise of the NPC, the 2014–2021 period is one where probation edges into the public sphere via extensive media coverage, including the considerable number of probationers or a string of protests by probation counsellors who felt overworked and overwhelmed. We continue the chapter by analysing the composition and the dynamics of the probation population, always looking beyond the mere numbers to other analytic markers (i.e. numbers of obligations and lengths of the probation period). We conclude the chapter by arguing that our discussion of the ‘weight’ of supervision adds to the current understanding of mass supervision by looking at the aggregated impact that different social, political, penal and cultural factors have on probation practice. In other words, large caseloads, limited human resources, precarious material conditions and negative organisational cultures are likely to generate supervision experiences that can be better interpreted by looking and thinking beyond numbers.

This chapter compares the current biodiversity practices of higher education institutions (HEIs) and their learning effects of the Global North and South. It particularly explores the HEIs’ strategies targeting biodiversity and ecosystem services preservation. In order to answer the research question, a qualitative content analysis of published sustainability reports of the systematically selected HEIs was performed. The Times Higher Education (THE) was used to select HEIs. The results show that biodiversity reporting and management is still in its early stages in HEIs from both the Global North and South and could benefit from further research and suggestions for improvement. One implication for the HEIs is that they could increase public awareness and knowledge of biodiversity through the integration of this topic into their curricula, more research projects on biodiversity, and operations on and off campus.

Artificial intelligence (AI) models are demonstrating day by day that they can find long-term solutions to improve wastewater treatment efficiency. Artificial neural networks (ANNs) are one of the most important of these models, and they are increasingly being used to forecast water resource variables. The goal of this study was to create an ANN model to estimate the removal efficiency of biological oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) at the effluent of various primary and secondary treatment methods in a wastewater treatment plant (WWTP).

The MATLAB App Designer model was used to generate the data set. Various combinations of wastewater quality data, such as temperature(T), TN, TP and hydraulic retention time (HRT) are used as inputs into the ANN to assess the degree of effect of each of these variables on BOD, TN, TP and TSS removal efficiency. Two of the models reflect two different types of primary treatment, while the other nine models represent different types of subsequent treatment. The ANN model’s findings are compared to the MATLAB App Designer model. For evaluating model performance, mean square error (MSE) and coefficient of determination statistics (R2) are utilized as comparative metrics.

For both training and testing, the R values for the ANN models were greater than 0.99. Based on the comparisons, it was discovered that the ANN model can be used to estimate the removal efficiency of BOD, TN, TP and TSS in WWTP and that the ANN model produces very similar and satisfying results to the APPDESIGNER model. The R-value (Correlation coefficient) of 0.9909 and the MSE of 5.962 indicate that the model is accurate. Because of the many benefits of the ANN models used in this study, it has a lot of potential as a general modeling tool for a range of other complicated process systems that are difficult to solve using conventional modeling techniques.

The objective of this study was to develop an ANN model that could be used to estimate the removal efficiency of pollutants such as BOD, TN, TP and TSS at the effluent of various primary and secondary treatment methods in a WWTP. In the future, the ANN could be used to design a new WWTP and forecast the removal efficiency of pollutants.