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This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

The purpose of this study is to analyze the two-dimensional blood flow in the artery slant from the axis at an angle with mild stenosis under the joint effects of the electro-osmotic, magnetic field, chemical reaction and porosity using a new analytical method. In addition, the mathematical model presented by the researchers Tripathi and Sharma (2018c) was successfully developed by adding the effect of electro-osmosis and studying the impact of the new addition in the developed model on blood flow.

A new analytical method was used to find the analytical approximate solutions of two-dimensional blood flow in artery slant from the axis at an angle with mild stenosis. This technique is based on integrating the Akbari-Ganji and the homotopy perturbation methods.

The results of axial velocity, concentration, temperature and the wall shear stress for blood flow were analyzed in the cases of the absence and presence of electro-osmosis. Furthermore, in these two states of electro-osmosis, a contour plot was created to show the difference in the profile of velocity to the flow of blood when the magnetic field was increased and the altitude of stenosis was increased. The results showed that the new technique is effective and has high accuracy to determine the analytical approximate solutions of two-dimensional blood flow in artery slant from the axis at an angle with mild stenosis. The validity, utility and necessity of the new method were illustrated from the graphs of the new solutions; in addition, there is an excellent agreement with the results of previous studies.

This paper focuses on developing the mathematical model which was presented by the researchers Tripathi and Sharma (2018c), by adding the effect of the electro-osmosis to it, which has been successfully developed. According to the authors’ modest information, the new system has not been studied before. This current problem is solved by using an innovative approach known as the Akbari-Ganji homotopy perturbation method (AGHPM) which has not been used before in two cases: the presence and absence of the effect of electro-osmosis. This new technique afford new with effective and has high accuracy results. Furthermore, the new study (i.e. adding effect of electro-osmosis) with the applications of (variable viscosity, magnetic field, chemical reaction and porosity) illustrated the importance of applying electro-osmosis and how doctors can benefit from it during surgeries through proper use.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

This study aims to investigate the effect of perceived insider status to employees' innovative behavior, the mediating role of knowledge sharing and the moderating role of organizational innovation climate in the relationship between knowledge sharing and employees' innovative behavior.

This study adopted questionnaires to gather data. The sample of 341 employees working in diverse organizations in China was applied to examine the hypotheses.

The results indicate that perceived insider status is positively related to employees' innovative behavior and knowledge sharing mediates the relationship between perceived insider status and employees' innovative behavior. In addition, organizational innovation climate enhances the relationship of knowledge sharing and employees' innovative behavior.

This study builds a system from psychological aspect to behavior, which includes the mechanism of the influence of perceived insider status on employees' innovative behavior and a cross-level analysis of the influence of organizational innovation climate on employees' innovative behavior, breaking through the previous research paradigm of a single level of climate and employee behavior.

The purpose of this paper is to investigate the effect of doping element on the structural, thermal properties, mechanical performance and the failure mechanism of hexagonal nano boron nitride (h-BN)-reinforced basalt fabric (BF)/epoxy composites produced by hand lay-up and vacuum bagging technique. h-BN particles doped to composite materials increased the tensile, bending and impact strength of the composite at certain rates while 1 Wt. % h- BN addition shows the highest tensile and flexural strength.

The epoxy resin was doped with h-BN nanopowder at the certain rates (0, 1, 2 and 4 Wt.%) and the epoxy: hardener ratios used in the study were selected as 80%: 20% by weight. Then, with the aid of a roller by hand lay-up method, a mixture of epoxy + hardeners containing nanoparticles and nanoparticle-free were fed onto BFs, 12 layers of each dimension 30 cm × 30 cm. The surplus epoxy resin was moved away from the composite sheets using the vacuum bagging process and left to cure at room temperature for 24 h. ASTM D3039 for tensile, D7264 for three-point bending and D256 for Izod impact test were performed for the mechanical tests. After the tensile test, the morphologies of the fracture surface were examined with a stereomicroscope and various failure mechanisms are highlighted.

In this study, a series of basalt/epoxy composites with h-BN nanopowders have been prepared to identify the effect of filler ratio on mechanical properties. It has been known from the results of mechanical experiments that the addition of h-BN improves the mechanical performance of materials at a certain rate. The tensile and flexural strengths of h-BN doped composites, increase for concentrations of 1 Wt.% h-BN, but decrease with the increasing content of it. The basalt/epoxy resin composite with higher mechanical properties could be a potential material in the automotive and aerospace industries.

The aim of this study is to contribute to literature within the context of this new combination of composites and their mechanical properties, failure mechanisms. It presents detailed characterization of each composite by using X-ray differaction (XRD), differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy.

Innovation for service contributes to service quality and customer satisfaction, and further benefits service-centered organizations to sustain competitive advantages. However, concurrent mediating and moderating mechanisms underlying innovation for service at both the group and individual levels have been scarcely investigated. The purpose of this study is to explore multilevel mediating and moderating mechanisms behind the relationship between dual-level transformational leadership (TFL) and innovation for service at the group and individual levels.

Data were collected from two countries (i.e. China and Australia). Multilevel structural equation modeling was employed to validate the research model. Bootstrapping with 5,000 replications and latent moderated structural equation modeling were used to respectively examine the mediating and moderating mechanisms.

The cross-national results showed that task interdependence and creative role identity respectively played as the group-level and individual-level mediating roles between TFL and innovation for service. It was also found that task interdependence played as a cross-level predictor enhancing individual innovation for service. Task interdependence was a moderator on the relationship between individual-level TFL and creative role identity among Australian employees, but not among Chinese employees. The relationship between creative role identity and individual innovation for service was not moderated by task interdependence among both Chinese and Australian employees.

This study contributes to advancing the TFL–innovation research through revealing dual-level TFL as the antecedent of innovation for service at both the group and individual levels. It also extends the understandings of the mediating and moderating mechanisms behind this dual-level relationship between TFL and innovation for service.

This paper aims to investigate the influence of human resource management (HRM) practices on the level of innovativeness observed within the service sector of Ghana, taking into account the potential mediating role of innovation capability.

The research used a quantitative methodology to fulfill the study's objectives. A Web-based survey questionnaire was designed to gather data from a sample of 168 respondents, selected through a convenient sampling technique. The proposed model was tested using the Process Macro Model 4 by Hayes in SPSS version 26.

The study’s outcomes indicate that there is no statistically significant correlation between HRM practices and firm innovativeness. However, the mediating role of innovation capability was observed to fully account for the relationship between human HRM practices and firm innovativeness. Additionally, a positive and significant association was identified between HRM practices and innovation capability, as well as between innovation capability and firm innovativeness.

It is important to note that the findings are limited to the perspective of employees within the service sector of Ghana. Therefore, future research could explore the manufacturing and/or extraction industries in Ghana to obtain a more comprehensive understanding. Furthermore, a larger sample size could be considered in future studies.

To the best of the authors’ knowledge, this study presents a novel examination of the hypothesized model within the Ghanaian context, providing valuable insights into the relationship between HRM practices, innovation capability and firm innovativeness.

The research is geared towards studying the impact of “GDP per capita (GDP)”, “energy consumption (EC)”, “human capital (HC)” and “trade openness (TO)” on India's ecological footprint (EF) from 1997–1998 to 2019–2020.

The autoregressive distributed lag model (ARDL) bound test was used to look at the short-run and long-term coefficients and the cointegration of the variables.

The results depicted a long-run connection between the variables. The long-run results found a favourable relationship between GDP, EC and EF, indicating that economic growth through heavy reliance on fossil fuels contributes to environmental unsustainability. An inverse relationship between HC, TO and EF was also observed, indicating that education fosters pro-environmental behaviour and leads to adopting cleaner technology that contributes to environmental sustainability.

The research substantiates India's pressing requirement for sustainable development, ensuring a harmonious balance between economic performance and environmental preservation. A carefully designed policy needs to be formulated to mitigate emissions stemming from growth in India. Policymakers are urged to implement measures that promote ecologically friendly tools, utilities and transportation to curb long-term environmental degradation.

The study is novel, incorporating an exhaustive review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study further examines how India's EF is affected by its HC; the preceding literature has yet to discuss much about the connection between HC and the environment. Finally, the study employed advanced econometric techniques, namely the cointegration technique and ARDL model, to find the relationship between EF, GDP, HC, EC and TO.

The interaction of systems through a designated control channel has improved communication, efficiency, management, storage, processing, etc. across several industries. The construction industry is an industry that thrives on a well-planned workflow rhythm; a change in the environmental dynamism will either have a positive or negative impact on the output of the project planned for execution. More so, raising the need for effective collaboration through workflow and project planning, grid application in construction facilitates the relationship between the project reality and the end users, all with the aim of improving resources and value management. However, decentralisation of close-domain control can cause uncertainty and incompleteness of data. And this can be a big factor, especially when a complex project is being executed.

This research intends to develop a model for predicting employees at a high-risk attrition and identify the most important factors affecting them.

In this study, using the triangulation technique of a mixed research method, the employee attrition problem is investigated by identifying its affecting factors. For that matter, data related to the human resources department of a pharmaceutical company in Iran are used. And to achieve the intended goal, advanced data mining algorithms and interviews with human resource managers are applied.

A model for predicting employees at a high-risk attrition is presented based on the gradient boosting machine algorithm with 89% accuracy. The use of the mixed research approach shows that qualitative and quantitative methods can be more effective in identifying the factors affecting employee churn or loss of staff. The results also contain a new situation arising out of the COVID-19 pandemic and remote working scenarios having impact on employee attrition. Finally, human resource policies are presented based on variables related to each of the identified factors.

The novel contributions of this study include real data related to a leading pharmaceutical company as well as a combination of two quantitative and qualitative methods. The hybrid approach can identify the reasons for attrition and, consequently, retention policies to benefit from the advantage of both approaches. Data mining can be useful to identify the factors, which are usually not mentioned in termination interviews, such as direct managers. On the other hand, the results obtained from termination interviews can also include features that the authors cannot identify through data mining, which are specifically related to the characteristics of the pharmaceutical industry such as building a more professional career path. From a practical perspective, since this company specializes in pharmaceutical marketing in a new way and is primarily comprised graduates, it is important to note that the churn of specialized people disperses organizational and technological know-how. On the other hand, the pharmacist community in Iran is small, and their attrition might adversely affect not only the reputation of an organization but the employer's brand as well. So, this research would help other similar firms in retaining their valuable human capital.