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The paper aims to identify the effect of ignorance of correlatedness among process observations and to implement new sampling schemes; skip and mixed sampling, in order to reduce the effect of autocorrelation on process capability index (PCI) Cpm.

Autocorrelated observations are generated using autoregressive process of order two (AR (2)) using Monte Carlo simulations. The PCI is computed based on these observations assuming the independence. The skip and mixed sampling schemes are then used to form sub-groups among correlated observations. The PCI obtained using sub-groups from skip and mixed sampling schemes are assessed using sample mean and sample standard deviation.

The paper provides empirical insights into how the effect of autocorrelation decreases in the estimated value of PCI Cpm. The use of new sampling schemes, skip and mixed sampling, reduces the effect of autocorrelation on estimates of PCI Cpm.

This paper fulfills an identified need to study how to reduce the effect of autocorrelation on PCI Cpm.

This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.

The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.

The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.

This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.

This research aims at explaining the phenomenon of the “black children” (heihaizi), a very little-known generation who lived with concealment under the one-child policy in China. The one-child policy was officially introduced to nationwide at the end of 1979 by permitting per couple to have one child only, later modified to a second child allowed if the first was a girl in rural China in 1984. It was officially replaced by a nation-wide two-child policy and most existing research focused on the parents’ sufferings and policy changes. The term “black children” has been mainly used to describe their absence from their family hukou registration and education. However, this research aims at expanding the meaning of being “black” to explain the children who were concealed more than at the level of family formal registration, but also physical freedom and emotional bond. What we do not yet know are the details of their lived experiences from a day-to-day base: where did they live? How were they raised up? Who were involved? Who benefited from it and who did not? In this way, this research challenges the existing scholarship on the one-child policy and repositions the “black children” as primary victims, and reveals the family as a key figure in co-producing their diminished status with the support of state power. It is very important to understand these children’s loss of citizenship and human freedom from the inside of the family because they were concealed in so many ways away from public view and interventions. This research focuses on illustrating how their lack of access to continued, stabilized, and reciprocally recognized family interactions framed their very idea of self-worth and identity.

This paper investigates the interactional relationships between sustainable human resource management (SHRM) and organizational performance (OP). Sustainable HRM is an approach that links HRM and sustainability. These studies focused on integrating HR with sustainable developments, such as economic and social aspects, in favour of focusing on the environmental aspect. Organizational change is an ongoing process that has to be managed effectively to keep the change in place for a long time.

A framework was offered to estimate the cause-and-effect relation of the SHRM and OP factors. Data is gathered from professionals from various pharmaceutical industries. This study applied two methods, Fuzzy AHP and DEMATEL Type II. These techniques are used to understand the cause-and-effect factors and their interactions.

It was observed from the findings that the factor of SHRM, such as Social Justice (F2), Green Job Design (F5), Green Training (F6) and Implementation of Green Policy (F8), was the most critical for the pharmaceutical sector that effects Financial performance (F13), Customer Satisfaction (F15) and Market performance (F14). Pharmaceutical firms ought to coordinate public health advocacy efforts, engage in healthcare initiatives and provide financial support for environmentally friendly efforts that improve social and economic conditions.

For this sustainability, managers concentrate on creating an environment that is healthy and acceptable, and they work hard to mitigate the impact of natural factors and repair damage done to the environment; it is essential to move towards sustainable development to resolve environmental problems. Improving HR efficiency is among essential HRM responsibilities, as they expand the knowledge base of the workforce, enhance human capital, and eventually create valuable intangible assets and promote and encourage sustainable pharmaceutical products for some years.

This research paper has presented exclusive worth to the SHRM and organizational performance literature as it employs fuzzy FAHP and DEMATEL type 2. There is less research on SHRM in the pharmaceutical sector with these factors. In addition, FAHP and TYPE 2 DEMATEL are used in very few researches on SHRM approaches.

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

This paper aims to examine whether China's grain price support policy has distorted the grain market price.

The time-varying differences-in-differences (DID) model is used to study the impact of support policies on grain prices, and it is combined with the event study method to explore the dynamic effects of price support policy. Panel data model is used to study the effect of the price support policy on price formation for national grain market prices. In addition, we apply the smooth transformation (STR) model to verify whether there is a distortion in the transmission of grain prices among different markets in China and from the international market to China’s market.

China’s grain price support policy plays a significant role in rising grain market prices, weakens the decisive role of the market mechanism in the formation of grain prices, hinders the spatial transmission of market price signals and decreases the effect of price transmission from the world market to China’s market.

In order to ensure both the stability of grain production as well as the market stability, and also to ensure that intervention policies do not distort the food market, the minimum purchase price of grain and market regulation policies should be adjusted as follows: (1) price support policy should be shifted to an income support policy and (2) reasonably determine the scale of reserves and implement a grain minimum purchase price policy in limited areas.

Our findings are relevant for understanding the effect of China's grain price support policies on the implementation regions and the price transmission effect, which provide reference experience for developing countries to implement food price policies.

The purpose of this study is to examine the continuance intentions of working professionals to pursue e-learning courses as a path for career advancement. The primary objective of this study is to ascertain the predictors of continued intentions of working professionals to pursue e-learning courses and examine if this is a trend in career development.

Perceived usefulness of e-learning, motivation and satisfaction are independent variables which are examined using a regression model as potential determinants of continued intentions to use various e-learning platforms. Data from 240 working professionals in different sectors was collected. In addition, satisfaction, motivation and perceived usefulness among the male and female respondents are compared using ANOVA.

The findings showed that motivation, satisfaction and perceived usefulness of e-learning are significant predictors and have a strong influence on the continued intentions of working professionals to pursue e-learning courses. In addition, the results showed that motivation levels while pursuing e-learning and satisfaction derived from them were higher for female professionals.

This study identifies the antecedents of the continued intentions of working professionals to pursue e-learning courses on the path of career advancement. The outcome of the study can be used by educators and e-content creators to make e-learning more engaging. Corporates can also use the results of this study to identify initiatives that can encourage the pursuit of e-learning.

This study provides an important insight exploring the antecedents of continued intentions of working professionals to pursue e-learning courses as a path of career advancement. The research contributes significantly to the understanding thought process of working professionals towards their careers.

The concept of ubiquitous assimilation in e-commerce, denoting the seamless integration of technologies into customer shopping experiences, has played a pivotal role in aiding e-satisfaction and, consequently, fostering patronage intention. Among these, text-based chatbots are significant innovations. In light of this, the paper aims to develop a conceptual framework and comprehend the patronage behaviour of artificial intelligence-enabled chatbot users by using chatbot usability cues and to determine whether the social presence and flow theories impact e-satisfaction, which leads to users’ patronage intention. The current research provides insights into online travel agencies (OTAs), a crucial segment within the travel and tourism sector. Given the significance of building a loyal clientele and cultivating patronage in this industry, these insights are of paramount importance for achieving sustained profitability and growth.

The research framework primarily focused on the factors that precede e-satisfaction and patronage intention among chatbot users, which include social presence, flow, perceived anthropomorphism and need for human interaction. The researchers collected the data by surveying 397 OTA chatbot users by using an online questionnaire. The data of this cross-sectional study were analysed using covariance-based structural equation modelling.

Findings reveal that e-satisfaction is positively linked with patronage intention and the variables of social presence and flow impact e-satisfaction along with chatbot usability cues. There were direct and indirect relations between chatbot usability and e-satisfaction. Moreover, the personal attributes, “need for human interaction” and, “perceived anthropomorphism” were found to moderate relations between chatbot usability cues, social presence and flow.

The impact of chatbot’s usability cues/attributes on e-satisfaction, along with perceived attributes – social presence and flow in the realm of OTAs contributes to the human–chatbot interaction literature. Moreover, the interacting effects of perceived anthropomorphism and the need for human interaction are unique in the current contextual relations.

This paper aims to explore the effectiveness of ethnically targeted ads in developing consumer–brand relationships through an application of social identification theory and elaboration likelihood model among African American consumers in the service sector.

Study 1 used a 2 (service type: hedonic vs utilitarian) × 2 (strength of ethnic identification: high vs low) between-subjects experimental design. Study 2 used the same experimental design, procedure and ads as Study 1.

Taken together, the findings from these two studies demonstrate how ethnically targeted advertising, in conjunction with service type, can influence consumer–brand relationships. The results showed that those with high strength of ethnic identification had more brand love, as well as higher intentions to spread positive word-of-mouth, purchase intention and brand loyalty for hedonic services, but that this effect was not significant for utilitarian services.

The environments in which advertisements appear (e.g. in an in-store display or a magazine advertisement) is important, and consumers’ reactions to targeted ads in various environments should be considered in future research. Future studies should also examine the role of individuals’ personality traits and level of acculturation in determining their relationships with brands.

Across two studies, the authors demonstrated that ethnic ads are more effective for African American individuals with high level of ethnic identification especially for hedonic services.