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Being clear and specific on what moderating and/or mediating variables are included and what effects are observed in academic research helps the reader to better understand the academic research context and results. But in terms of managerial relevance, it is also important to do this in a way that it provides descriptive, goal and operational relevance to decision makers in practice, depending on the type of intended research. This article wants to provide “a question-based step-by-step guide” on how to make the analysis of moderating/mediating variables and their observed effects more managerially relevant.

Based on a critical review of the literature, important criteria of managerial relevance are confronted with important aspects of theory building with respect to mediating and moderating effects, leading to best-practice insights and recommendations. Moreover, exemplary articles are used to illustrate these findings.

The insights and step-by-step recommendations assist the academic researcher in making choices when analyzing moderators and mediators, by not only taking a theoretical perspective, but also a managerial (relevance) perspective. Adding moderators/mediators may for instance challenge the “core logic of managerial practice” (in terms of thinking and decision making), even if it does not change the “core logic of a theory” as such. In the other direction, academics (and their theory) may be challenged by practitioners, in the way they define moderators/mediators and their levels. The steps in this article relate to aspects such as measurability, controllability and role of moderators and mediators in managerial problem and decision contexts. In case of multiple moderating and/or mediating variables, the decision architecture for managers becomes more complex, especially when the effects are countervailing/opposite. Multiple studies in this article illustrate that in that case, making optimal decisions becomes a “balancing” act for managers/decision makers and may even challenge their common beliefs (e.g. linear thinking).

The guidelines on managerial relevance of moderating and/or mediating variables and their effects can be used by academic researchers and editors of academic journals, pursuing not only academic rigor, but also managerial relevance. Besides being a guide for managerially relevant output, it also helps in determining for which questions in the research process, input from practitioners or at least insights from practice (e.g. through sources such as business magazines and portals) may be needed. The guidelines may also be used for teaching purposes, complementing more theoretical articles that mainly focus on methodological/statistical issues of moderating/mediating variables and their effects.

The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya.

The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs.

The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable.

A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent.

While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXCR) and private capital inflows have a significant effect on the changes in HPs. Nonetheless, the study adds two little-known indicators in the projection of HPs, which are the EXCR and HHI.

Theory is an essential prerequisite in the development and maturation of any scholarly discipline. This study offers insight into theory development in reverse logistics (RL) studies, provides a synopsis of the theories employed in RL studies, and presents a comprehensive framework for choosing and applying theories in RL studies.

Using the systematic literature review approach, 265 various RL articles were analysed to discover the trend in using theories in RL studies and classify the individual theories employed. The analysis of the theoretical classification is presented to explain the type and frequency of the usage of theories.

The analysis discovered 52 specific theories from the sample. These theories were categorised under various categories: competitive, inventory, economic, decision, etc. The institutional, stakeholder, transaction cost economies, resource-based view, natural resource-based view, dynamic capability, agency and theory of planned behaviour were some of the key theories discovered. Finally, a comprehensive framework is provided to aid researchers in choosing and utilising theories.

This study gives authors, reviewers and editors perspectives on utilising theories in RL studies. It will give them the impetus to develop theories in RL and limit the borrowing or extension of theories from other disciplines to RL studies.

To the best of the researcher's knowledge, this is the first attempt to comprehensively provide an anatomical perspective into theory usage in RL studies. Besides, this study's proposed framework for selecting and using theories is a novelty in the domain of RL.

Motivated by concerns and the ongoing debate regarding auditors’ independence and impartiality, this paper aims to examine the impact of the financial crisis on non-audit services (NAS) provision and audit quality (main and robust variables) in the four largest Eurozone countries together during the global financial crisis (GFC).

The authors used a time trend OLS model with a dummy variable as well as a baseline model with a dummy and control variables accounting for multicollinearity, considering the characteristics of the GFC.

It documented a positive (negative) relationship between NAS provision (audit quality) and crisis in four Eurozone countries, Germany, France, Italy and Spain, in the context of a baseline approach, supporting the hypotheses that there are higher non-audit fees and a lower audit quality. Moreover, it is revealed that NAS provision and audit quality behave similarly, using a time trend approach, during the GFC. Considering the role of the auditor specialization or not (Big4 vs non-Big4) in companies, a significant effect from crisis on non-audit fees and audit quality for the four countries under the baseline approach is found. In general, the findings persist for NAS provision and audit quality using the robust methods of the time trend and panel OLS approaches. Multicollinearity was not found to affect the findings of the regressions.

The study provides important implications for firm managers, auditors and regulatory authorities.

To the best of the author’s knowledge, it is the first time that the impact of the crisis on non-audit fees and audit quality is investigated during the GFC with two sets of OLS models (a time trend OLS with a dummy and a panel OLS with a dummy and control variables) in four largest Eurozone countries together.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

This study aimed to know the effect of cross-sectional risk, which comprises business-specific risk and stock market volatility, as a variable for estimating macroeconomic risk in Indonesia. This study observes public companies in Indonesia and Indonesian macroeconomic data from 2004 to 2020. In this study, the author uses term spread as the dependent variable that reflects macroeconomic risk. The cross-sectional risk comprises financial friction (FF), cash flow (CF), debt–service ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag (ARDL) Model method, this study shows that business-specific and stock market risk can estimate macroeconomic risk, so that it becomes an early signal of economic shock, such as recession or high inflation, in the future. The model in this study also examines the cross-sectional risk relationship with other macroeconomic indicators, such as the Consumer Confidence Index (CCI), money supply (M0), and Indonesia’s trade balance (TB).

This chapter focuses on testing optimal capital structure theory: The role of intervening variable debt to equity ratio (DER) on the influence of the financial performance, Ownership Structure of Independent Board of Commissioners (IBCO), Audit Committee (ACO), and Institutional Ownership on Firm Value. The research design was explanatory research using path analysis. Using purposive sampling, 61 manufacturing companies, observation period from 2014 to 2018 with 286 N samples. The research novelty empirically can prove the role of intervening variable DER on the effect of return on assets (ROA) on firm value and shows the market response to the ROA is fully reflected by DER, indicating the existence of an optimal capital structure. The role of DER on the effect of ROE and IBCO on firm value is a partial mediation with the inverse direction. This phenomenon shows that the mechanism of forming a balance between the responses of investors and creditors relates to debt financing.

This paper tests if there exists a subjective well-being gap between informal workers in the informal and formal sectors in urban China, and explores the mechanisms behind such differences.

The author develops a simple theoretical model to analyze the effects of the employment sector and work time flexibility on workers' happiness and conducts a descriptive study to examine the relationship between employment type and subjective well-being using the China General Social Survey (CGSS) 2010, 2013, 2015 and 2017 datasets, a nationally representative sample.

The results show that only dependent informal work in the formal sector impairs workers' happiness, while the effect of independent informal work is not statistically significant. The potential mechanisms suggest that independent informal workers have higher working time flexibility and can work more hours to increase their earnings, which increases their subjective well-being. However, it is difficult for dependent informal workers to earn more by working more hours due to poor working time flexibility.

This study indicates that informal workers in the formal sector have lower subjective well-being in urban China and deserve more attention from policymakers. The author also suggests that increasing working time flexibility and encouraging self-employment can contribute to the welfare of informal workers.

This paper aims to analyze the impact of the adoption of ISO 14001 and ISO 9001 on the performance of Portuguese companies. The sample includes the companies listed on Euronext Lisbon, with economic, financial and specific information – the specific being environmental information and quality information – for the period between 2015 and 2019, which corresponds to the post-Troika period when some economic growth started to be witnessed. The specific information of each area is translated into the environmental certification by the ISO 14001 standard, the quality certification by the ISO 9001 standard, and sustainability reports.

To achieve this aim, four variables were used as a measure of the companies' performance, Return on Assets (ROA), Return on Equity (ROE); Tobin's Q and EBITDA Margin. With this data, different panel models were tested to validate if ISO 9001 and ISO 14001 certifications impact Portuguese listed companies performance. Specifically, the authors have used the Generalized Method of Moments, GMM-System, an estimation method proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results show that, in general, the environment and quality variables fail to explain the dependent variables, that is, ISO certifications do not provide positive or negative variations in the performance of companies, suggesting that they are not yet as much for civil society, as well as for current or potential shareholders. When used as an independent variable, certification according to the ISO 14001 or 9001 standards, negative and significant oscillations were verified in the dependent variable, MgEBITDA, suggesting that only for managers this variable is determinant, but with a negative impact, given the high costs, it entails without pressure from other stakeholders.

This study is the first to analyze the impact of the adoption of ISO 14001 and ISO 9001 on Portuguese companies' performance. This empirical study aims to show all investors, managers, regulators and civil society itself the long path that still needs to be taken toward sustainability.

Nowadays, there is a strong public interest in promoting transparency to be informed about the actions of the public sector. At the same time, there has been a significant change in society’s perceptions and concerns about sustainable development, with a marked increase in attention to this area. In this context, our main objective is to investigate the impact of transparency practices in local government on the implementation of the Sustainable Development Goals (SDGs) in Spanish municipalities.

We will analyse a sample of 84 municipalities, using the Dynamic Transparency Index published by Dyntra to measure transparency. For the level of implementation of the SDGs, we will use an index specifically created using data from the report “The SDGs in 100 Spanish Cities”, published by the Spanish Network for Sustainable Development in 2020.

Municipalities with a larger dependent population tend to achieve higher SDG levels. Municipalities with lower financial surpluses and more self-generated resources show better SDG implementation. Progressive political parties lean more towards sustainability, and coalition governments show higher SDG implementation than majority governments. Gender appears to play a minor role in SDG implementation, but male leadership is associated with higher levels. Factors such as population density and government transfers do not have a significant impact on SDG implementation levels.

This study seeks to address the lack of empirical research on the potential impact of transparency on the achievement of the SDGs, while also taking into account other socio-economic, financial and political aspects of the municipality. In doing so, it also contributes to the limited empirical literature on the determinants of the level of SDG implementation in local governments.