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To better understand the relationship between the headquarters and subsidiaries of multinational corporations, we introduce and test a theoretical framework that builds on and extends the positive agency theoretic corporate governance literature. Results indicate that there are three types of subsidiary bundles of corporate governance mechanisms that are used by multinational corporations. In addition, the following factors can help predict what type of subsidiary bundle a multinational corporation will use to align the interests of its headquarters with a particular subsidiary: the multinational corporation’s international strategy, its subsidiary’s importance, environmental uncertainty faced by its subsidiary, and its subsidiary’s age.

This study is aimed at examining the effect of Total Quality Management (TQM) practices on the operational performance of ISO 9001:2008 certified manufacturing companies in Ethiopia.

A cross-sectional survey was conducted to meet the purpose. Primary data was collected from the managers and senior experts working under the production and quality management units of the surveyed firms. Data was obtained from a survey of 302 participants found in 73 ISO 9001:2008 certified manufacturing organizations. Both EFA and CFA were applied to validate and confirm the instrument, and Structural Equation Modeling (SEM) was used to test the hypotheses.

The results revealed that among the practices of TQM used in the model only supplier quality management, continuous improvement and process management were found to have significant and positive effect on the operational performance of the ISO 9001:2008 certified manufacturing organizations in Ethiopia.

Future studies are suggested to consider some contextual variables such as firm age, scope of operation, firm size and firm strategy while addressing the objective.

The study will encourage managers of manufacturing companies in Ethiopia to utilize a reliable and valid framework of TQM practices for better operational performance results.

The fact that Ethiopian manufacturing organizations are required to improve their product's quality in order to improve their productivity and enhance their competitiveness in a global market is the rationale of this study. Even though several studies have evolved to scrutinize the link between TQM and operational performance across the world, nearly nothing, is known about this linkage in Ethiopia. Thus, the study represents one of the first attempts to empirically investigate this linkage in Ethiopian context.

The purpose of this paper is to investigate cotton fabric behavior that is exposed to radar waves between selected operation frequencies as an alternative radar-absorbing material (RAM) response. Cotton fabric biocomposite materials were compared with carbon fabric composite materials, which are good absorbers, in terms of mechanical and electromagnetic (EM) properties for that purpose.

The laminated composite plates were manufactured by using a vacuum infusion process. The EM tests were experimentally performed with a vector network analyzer to measure reflection, transmission and absorption ability of cotton fabric, carbon fabric and cotton–carbon fabric (side by side) composite plates between 3 and 18 GHz. The tensile and low-velocity impact tests were carried out to compare the mechanical properties of cotton fabric and carbon fabric composite plates. A scanning electron microscope was used for viewing the topographical features of fracture surfaces.

The cotton fabric composite plate exhibits low mechanical values, but it gives higher EM wave absorption values than the carbon fabric composite plate in certain frequency ranges. Comparing the EM absorption properties of the combination of cotton and carbon composites with those of the carbon composite alone, it appears that the cotton–carbon combination can be considered as a better absorber than the carbon composite in a frequency range from 12 to 18 GHz at Ku band.

This paper shows how cotton, which is a natural and easily supplied low-cost raw material, can be evaluated as a RAM.

The direction of the causality relationship between Foreign Direct Investment (FDI) and economic growth is a highly controversial issue in the literature. There are two basic approaches advocating different causal directions between FDI and growth, which are called hypotheses of FDI-led Growth and Growth-led FDI. The aim of this study is to analyze the causality relationship between FDI and economic growth in RCEP countries and thus make a new contribution to the discussions in the relevant literature. In addition, the results of the study are expected to provide important implications for the policies to be designed for economic growth based on FDI flows to RCEP countries. Thus, by examining the direction of causality between FDI and economic growth in RCEP countries, we aim to provide a new contribution to related literature and make some implications for the policy design process of economic growth in the RCEP area.

We empirically examined the direction of a causal link between FDI and economic growth in the context of Regional Comprehensive Economic Partnership (RPEC) countries in order to test the hypothesis of FDI-led growth and Growth-led FDI. Accordingly, as our main variables of interest, we incorporated the inward foreign direct investment stock to gross domestic product ratio (FDI) and gross domestic product per capita (GDP). Hatemi-J (2012) asymmetric causality test has been employed in the investigation of the direction of causality between FDI and GDP over the period of 1980–2020. Thus, unlike most of the studies investigating the direction of causality between FDI and growth using the linear causality analysis method, our study performed a nonlinear causality analysis.

Empirical results reveal that the causal relationship between FDI and national income in RPEC countries is non-linear or asymmetric . The results of the symmetric causality test for both from FDI to national income and from national income to FDI are statistically insignificant for all countries. Therefore, this finding obtained from the study provided an important guide to the econometric methods to be used in other studies to be conducted in the same region in the future. Concerning the asymmetric causality relationship from FDI to growth, positive FDI shocks are an important cause of national income in most RCEP countries. However, the effect of negative FDI shocks on national income is quite weak compared to positive shocks. Regarding the asymmetric causality relationship from growth to FDI, positive national income shocks do not create a significant causal relationship with FDI. Similarly, the effects of negative national income shocks on FDI are statistically insignificant. Overall, asymmetric causality test results reveal that positive FDI shocks have an important causal impact on economic growth in most RCEP countries. Thus, the results of econometric analysis mostly support the argument that the FDI-led growth hypothesis rather than the Growth-led FDI hypothesis in RCEP countries. Accordingly, policy-makers in most of the RCEP countries should continue to provide more incentives and facilities to multinational companies in order to ensure constant economic growth.

Our study brings a significant difference in the econometric method used compared to most of the other studies in the literature. Existing empirical studies on the direction of causality between FDI and growth mostly use standard Granger-linear causality-type tests to detect the direction of causality among FDI and growth. Unlike most of the studies in the literature, our study adopted a different methodological approach, namely the Hatemi J test to detect the non-linear causality between FDI and economic growth in RCEP countries. Therefore, this paper made a new methodological contribution significantly to the literature focusing on the causal relationship between FDI and economic growth by using a non-linear causality method rather than a linear causality one.

Consumer expectations of quality have grown in recent years, forcing organisations, both service and manufacturing, to adopt total quality management (TQM) principles to satisfy customer demands efficiently. However, previous studies on the performance impacts of total quality management practices have mainly focused on the financial performance of firms in the manufacturing sector. This study focusses on the research questions: (1) What is the effect of TQM practices on operational performance? and (2) How do TQM practices combine to influence the operational performance of healthcare facilities?

Using a sample of 154 health facilities (i.e. private hospitals, pharmacies, maternity clinics, and diagnostic centres), the authors applied symmetric (PLS-SEM) and asymmetric (fsQCA) data analysis approaches to examine how TQM practices influence the operational performance of health facilities in the Ashanti Region of Ghana.

The PLS-SEM results revealed that five out of the seven TQM practices investigated influenced operational performance. However, the fsQCA results identify five different complex combinations of TQM practices that lead to operational performance.

Longitudinal studies can be conducted in the future to assess changes in the variables over time. A control variable, such as firm size, should be considered to assess the level of implementation of TQM practices based on firm size. A different performance measure, for instance, sustainability indicators or the balance score card, could be used to examine performance.

A proper and coordinated integration of the TQM practices is required for firms to be able to achieve operational performance. TQM practices vary in their sufficiency for operational outcomes; therefore, management needs to carefully consider their implementation as part of the organisation's strategy.

This research, by focussing on TQM practices from both symmetrical and asymmetrical perspectives, contributes to the understanding of the literature on TQM, thereby providing actionable insight on how to invest in the various TQM practices for improved operational performance.

This research aims to reveal the relationship between ingroup favoritism, seen as a theoretical cause of workplace violence experienced by physicians, with pre-violence, the moment of violence and post-violence, and the role of psychological resilience in coping with workplace violence.

A descriptive, cross-sectional design was applied in the research. First, data was gathered via structured questionnaire surveys to the 169 physicians and 321 patients with appointments using the simple random sampling method in three public hospitals in the province of Sanliurfa-Turkey between June 3, 2020, and January 1, 2021. The data was then examined through variance-based structural equation modeling and regression analysis.

Results indicate that the psychological resilience of physicians is essential in coping with workplace violence. The causes of favoritism behaviors were stated as a desire to protect the individuals they are with, increase their power, gain interest and cover their incompetence. It was determined that favoritism behaviors increase violence, but psychological resiliency decreases violence.

Some unobservable markers that impose priority for a patient from one's primary group, favoritism, may predict behaviors including violence. Contrary to popular belief, violence against physicians may be prevented by hospital management and social psychology practices rather than taking legal actions or increasing physical safety procedures. Moreover, the simultaneous collection of the data used in the study from physicians and patients with an appointment makes the study more meaningful and unbiased.

This study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.

This study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.

The analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.

This study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

This study aims to address the limited understanding of the complex correlations among strut size, structural orientation and process parameters in selective laser melting (SLM)-fabricated lattice structures. By investigating the effects of crucial process parameters, strut diameter and angle on the microstructure and mechanical performance of AlSi10Mg struts, the research seeks to enhance the surface morphologies, microstructures and mechanical properties of AM lattice structures, enabling their application in various engineering fields, including medical science and space technologies.

This comprehensive study investigates SLM-fabricated AlSi10Mg strut structures, examining the effects of process parameters, strut diameter and angle on densification behavior and microstructural characteristics. By analyzing microstructure, geometrical properties, melt pool morphology and mechanical properties using optical microscopy, scanning electron microscope, energy dispersive X-ray spectroscopy and microhardness tests, the research addresses existing gaps in knowledge on fine lattice strut elements and their impact on surface morphology and microstructure.

The study revealed that laser energy, power density and strut inclination angle significantly impact the microstructure, geometrical properties and mechanical performance of SLM-produced AlSi10Mg struts. Findings insight enable the optimization of SLM process parameters to produce lattice structures with enhanced surface morphologies, microstructures and mechanical properties, paving the way for applications in medical science and space technologies.

This study uniquely investigates the effects of processing parameters, strut diameter and inclination angle on SLM-fabricated AlSi10Mg struts, focusing on fine lattice strut elements with diameters as small as 200 µm. Unlike existing literature, it delves into the complex correlations among strut size, structural orientation and process parameters to understand their impact on microstructure, geometrical imperfections and mechanical properties. The study provides novel insights that contribute to the optimization of SLM process parameters, moving beyond the typically recommended guidelines from powder or machine suppliers.

This study aims at examining the effect of total quality management (TQM) practices on the financial performance ISO 9001:2008 certified manufacturing companies in Ethiopia with a mediating role of operational performance.

A cross-sectional survey research was conducted to meet the purpose. Data used for the study were solely primary data and were collected from the top and middle-level managers of different departments and senior experts working under the production/operation and quality management units of the target organizations. Data were obtained from 302 participants working in 73 companies using a self-administered questionnaire. Structural equation modelling (SEM) technique was applied to test the hypotheses positing the structural link between TQM practices, operational performance and financial performance.

The findings show that TQM practices had a significant direct and positive effect on both operational performance and financial performance and that operational performance significantly affects financial performance. The bootstrapping output of the mediation analysis also established that operational performance partially mediates the causal link between TQM practices and financial performance.

The empirical evidence provided by the present study provides helpful insights and guidance to managers to make a good deal of investment in maintaining enhanced performance outcomes under the operations stream that eventually would lead to better financial outcome.

Being one of the first attempts to empirically examine the structural linkages among TQM practices, operational performance and financial performance in Ethiopian manufacturing organizations, this paper provides strategic insights on the importance of implementing TQM practices in a holistic manner for the achievement of better performance outcomes.

Government incentives are critical for successful indigenous innovation commercialisation, yet there are concerns about the efficacy of these incentives. Therefore, this study examines the effectiveness of government incentives on successful indigenous innovation commercialisation in the context of low-income economies by testing the effects of demand and supply-side incentives on firm performance in the small-scale industry in Ghana.

The theoretical framework for this study is built on the below-the-radar theory of innovation (Kaplinsky et al., 2009). Using a sample of 557 firms engaged in commercialising various indigenous innovations in the small-scale industry in Ghana, PLS-SEM was deployed to assess 11 hypothesised paths based on a validated questionnaire.

The model results, at a 5% significance level, indicate that supply-side incentives are statistically insignificant on sales and profitability but have significant positive effects on employment. The direct and moderating influence of supply-side incentives and market factors on overall firm performance is also insignificant, while demand-side incentives to buyers have significant positive effects on all the performance metrics and positively moderate the effects of market factors.

The research focused on commercialising indigenous innovation in the context of low-income economies. Few studies, if any, have separately explored the effect of demand and supply-side government incentives on indigenous innovation in the context of low-income economies. The findings suggest that innovation support should focus more on the demand side of the innovation value chain.