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Some researchers regard discretionary accrual (DA) as one of the factors that drive corporate managers to conduct tax planning (Scott, 2009; Basri and Buchari, 2017). Based on agency theory and positive accounting theory, corporate managers can transform accounting information and manipulate firm earnings to reduce tax liability. There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of real earnings management (REM) on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning. Despite the widespread notion, as well as positive accounting theory, tax planning theory that financial attributes (profitability, leverage, liquidity and firm growth), REM and DA motivate tax planning, previous investigations have produced mixed results (Dwenger and Steiner, 2009; Wang and Chen, 2012; Chen and Zolotoy, 2014; Aghouei and Moradi, 2015; Pettersson and Wu, 2015; Ribeiro, 2015; Chen et al., 2016; Jamei and Khedri, 2016; Ogbeide, 2017; Yuniawati et al., 2017; Chen and Lin, 2017; Firmansyah and Febriyanto, 2018; Prastiwi, 2018; Rani et al., 2018; Kibiya and Aminu, 2019; Kałdoński and Jewartowski, 2019 and Siyanbonla, 2021). This study aims to use REM as a moderator to examine the relationship between financial attributes and tax planning whether it will strengthen or weaken the relationship.

The study examines the impact of financial attributes on the corporate tax planning of listed manufacturing firms in Nigeria. It also tests for the moderating effect of REM on the relationship between financial attributes and tax planning. Data for the study was sourced from the annual reports of sampled manufacturing firms. The study used the panel data methodology for analysis. The study used fixed effect estimation to interpret the parsimonious model and random effect was used to interpret the moderated model. The study documented that financial leverage has a positive significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other. The study recommends that firms should go for more debt to take advantage of the tax shield of interest on the debt. Also, firm management should use non-current debt to finance non-current assets and use current debt to finance current assets to avoid the risk of taking over or liquidation. The study also recommends that firm management should engage in intercompany and intracompany transactions by selling their goods to affiliates in countries with low prices and low tax rates. A firm should also overproduce goods to have high production costs and high closing inventory since real earning management significantly reduces tax liabilities by deferring income into a later year.

The study documented that financial leverage has a positive and significant influence on the tax planning of the sampled manufacturing firms. While firm growth has a negative but significant impact on the tax planning of listed manufacturing firms in Nigeria. REM has a positive and significant impact on tax planning. Also, REM moderate significantly the relationship between financial attributes on one hand and tax planning on the other.

There is a lot of research concerning earnings management and tax planning in the developed economy. These studies include Wang and Chen (2012) and Pettersson and Wu (2015). In the emerging economies, it includes Jamei and Khedri (2016), Kurniasih and Sulardi Suranta (2017), Prastiwi (2017), Almashaqbeh et al. (2018), Bayunanda et al. (2018), Rani et al. (2018) and Kałdoński and Jewartowski (2019). It is important to note that none of the research mentioned above has evaluated the impact of REM on tax planning in Nigeria. While in the developed economy only Kałdoński and Jewartowski (2019) used REM as an explanatory variable, while the majority of studies used DA. Consequently, no study has used REM to moderate the relationship between financial attributes and tax planning.

This paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.

The study uses panel data regression models on 40 companies between 1985 and 2021. The company's financial health is assessed using industry-standard financial ratios (i.e. measures of profitability, efficiency, solvency and liquidity) while controlling for economic factors such as national productivity, defense budgets and firm size.

The results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and the study's hypotheses for profitability and solvency. However, the effect of liquidity was the opposite of the expected result, possibly due to the defense industry's different view on liquidity compared to previous research.

The paper provides insights into the relationship between a prime contractor's financial health and its M&A spending, a topic with limited research. The findings can inform policymakers and regulators on the industrial base's future M&A activity, ensuring competitive markets that benefit the consumer.

In this article, the authors – a social studies methods professor and geography research associate – make the case for considering the integration of Holocaust geographies into the middle and secondary curriculum, potential challenges that teachers may have in teaching Holocaust geographies are addressed.

Using an experience in delivering professional development on Holocaust geographies to teachers to frame the discourse within the article, the authors contend that a study of Holocaust geographies tests geography as a discipline, addresses current problems and supports student inquiry. Therefore, the inclusion of the Holocaust in the geography curriculum is both needed and valuable.

Examining the Holocaust spatially using geographical skills moves students away from the potential limits of studying the Holocaust temporally using only historical skills. Thus, the distance between past and present, although not ignored, is narrowed through the inquiry into spatial patterns and characteristics, providing the potential to bring greater focus on present-day antisemitism, persecution, genocide and authoritarianism.

Educators are encouraged to take up work that intersects the civic goals of both geography and Holocaust education, yet literature on these intersections is sparse. We call upon Holocaust education and geography education organizations to develop and provide support for teachers around Holocaust geographies.

We model the relation between excess returns, fund size and industry size for active equity funds.

We study and contrast four markets – global equities, emerging markets, Australia core and Australia small caps – and use the results to investigate the extent to which funds deviate from estimated capacity.

We uncover a significantly negative relation between returns and both fund size and industry size across all markets. The estimated percentage of funds operating above versus below capacity varies both across markets and over time, as does the role played by fund size versus industry size. We find a greater prevalence of funds operating significantly below than above capacity, in contrast to findings for US equity mutual funds. Significant deviations from estimated capacity persist for a median of between two and six quarters.

Our main contribution is to show that the dynamics governing deviations from capacity for active equity funds vary across markets.

This research investigates the impact of Industry 4.0 technologies (I4.0) on the resilience of manufacturing firms against the COVID-19 pandemic. The study explores the mediating effects linked to the firm’s supply chain resilience and absorptive capacity in this relationship.

The empirical analysis involves 304 manufacturing firms and uses Partial Least Squares Structural Equation Modeling (PLS-SEM). A two-step hierarchical component model has been employed, considering the statistical analysis validation (reliability and validity) of the LOC and HOC models. The choice of the manufacturing industry is justified due to its degree of automation in emerging economies, such as Mexico, and its significant impact on job creation and the national gross domestic product.

The results confirm the positive impact of I4.0 technologies on companies’ resilience to COVID-19. They also support the indirect effects of the firm’s supply chain resilience and absorptive capacity. Absorptive capacity was found to have a higher significant indirect effect than supply chain resilience. Consequently, the study accentuates the significance of leveraging external knowledge and highlights the role of acquisition, assimilation, transformation, and exploitation capabilities in enhancing absorptive capacity.

The implications of this research extend to both manufacturing companies and public administrations, suggesting the need for I4.0 technologies implementation and supportive policies aimed at fostering absorptive capacity.

This research contributes to the literature by filling gaps in empirical studies in the context of developing economies. It provides valuable insights into the effects of I4.0 on absorptive capacity, supply chain resilience, and COVID-19 resilience, particularly in non-essential supply chains. It enriches the understanding of how I4.0 impacts the absorptive capacity and resilience of the supply chain during the COVID-19 crisis.

This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit.

This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables.

The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis.

The database is relatively small, which has limited a more thorough specification process and robustness tests.

Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).

The purpose of this paper is to provide a deeper understanding of the spatio-temporal behaviour of cruise passengers at a given destination using the city of Hamburg as a use case.

Big data in the form of passive location events from smartphones were analysed to determine the spatio-temporal behaviour of cruise tourists. The data were filtered using a definition created specifically for determining the signals of cruise passengers and were analysed using spatial statistics and network analysis methods.

In Hamburg, cruise passengers have a relatively small area of activity that is concentrated in the city's core tourist area. Foreign cruise passengers are less spatially concentrated than German passengers. Foreign passengers generate most of their visits at the airport and in the city's shopping areas, while German passengers are most frequently seen at the railway station and at the city's maritime experience locations.

Although numerous publications have examined the spatio-temporal behaviour of cruise passengers at the destination, to the best of the authors’ knowledge, no studies have used big data sources for this purpose. This paper uses passive location events from smartphones to determine the routes taken by cruise tourists in Hamburg, shows the strengths and weaknesses of this data source and suggests how cruise tourists can be defined from the data.

Selecting which processes to improve plays a critical role in the first phase of the business process management lifecycle, but it is a step with known pitfalls. Decision-makers rely on subjective criteria and their knowledge of the alternative processes put forward for selection is often inconsistent. This leads to poor quality decision-making and wastes resources. The purpose of this paper is to examine the proposition that decision-makers armed with context-enriched criteria make more logical, better-quality decisions. The context in question is qualitative, sensitive to decision-making bias and politically charged.

We applied a design-science approach, engaging 70 industry decision-makers through a combination of research methods to assess how different contextual configurations, in a hypothetical scenario adapted from the Australian banking industry, influenced and ultimately improved the quality of the process selection step.

The study highlights the impact of framing effects on context, and the need to adapt framing to decision-maker behavior and provides five guidelines to improve process selection effectiveness.

Process selection research to date has largely focused on quantitative evaluation techniques, with little attention paid to the role of context and the behavioral interplay of decision-making styles in practice.

This study evaluates how well Victorian local councils’ procurement policies align with the sustainable and circular economy (CE) approach that prioritises sustainable and regenerative practices. It proposes a set of criteria designed to effectively integrate environmental sustainability issues into purchasing policies.

Employing the Specific, Measurable, Assignable, Realistic and Time-bound (SMART) framework, a multi-dimensional content analysis guided by the goal-setting theory was applied to evaluate all 79 Victorian local councils’ procurement policies. This approach provided an assessment of policy specificity, measurability, assignability, realism and time sensitivity in promoting environmental sustainability through purchasing policies.

The findings underscored a significant deficiency in policy adherence to all SMART criteria concerning environmental sustainability, hindering the effective green purchasing decisions within government entities. This lack of integration of greening in purchasing policy poses challenges for manufacturers of waste-derived goods, obscuring the procurement objectives of these critical public sector customers.

The paper contributes to the sustainable procurement (SP) discourse by proposing guidelines aimed at improving the efficacy of governmental purchasing of sustainable products. These guidelines address the broader imperative to mitigate the environmental impacts of governmental spending on less sustainable goods, thereby fostering ecological sustainability and promoting responsible consumption.

While past studies have often relied on subjective content analysis methods, the SMART assessment used to develop the environmental sustainability criteria for purchasing policies, which distinguishes this study from previous governmental policy evaluation studies. This approach marks a departure from traditional governmental policy evaluation studies, offering a more structured analysis of policy effectiveness in promoting SP practices.

Knowledge loss (KL) is still an unfortunate fact, causing many challenges, including poor organisational performance, despite prior efforts to investigate knowledge retention methods. Therefore, this study identifies early approaches to combat KL and poor organisational performance, shifting focus on employee personality traits.

Grounded on the social exchange theory (SET) cross-section data from 400 Chinese construction knowledge employees were used to investigate the role of internal work locus of control (IWLC) on job rotation (JR), KL and organisational performance. The data were analysed through IBM SPSS Statistics 25 and SmartPLS 4 software.

The results demonstrated that IWLC minimises KL and positively influences JR. Then, JR negatively influences KL and decreases in organisational performance. The negative mediating effect of JR in the relationship between IWLC, KL and decreased organisational performance were also found. Finally, KL proved to positively influence a decrease in organisational performance.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees' behaviours to establish progressive collective learning and knowledge sharing.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees’ behaviours to establish progressive collective learning and knowledge sharing.

This study is the first attempt to explore the influence of personality traits in the early minimisation of KL, particularly the role of IWLC and JR in combating KL and improving organisational performance.