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The purpose of this paper is to analyse the transient effects in a functionally graded photo-thermoelastic (TE) medium with gravity and rotation by considering two generalised TE theories: Lord–Shulman (LS) and Green–Lindsay (GL). The governing equations are derived in rectangular Cartesian coordinates for a two dimensional problem.

All the physical properties of the semiconductor are supposed to vary exponentially with distance. The analytical solution is procured by employing normal mode technique on the resulting non-dimensional coupled field equations with appropriate boundary conditions.

For the mechanically loaded thermally insulated surface, normal displacement, stress components, temperature distribution and carrier density are calculated numerically with the help of MATLAB software for a silicon semiconductor and displayed graphically. Some particular cases of interest have also been deduced from the present results.

The effects of rotation and non-homogeneity on the different physical fields are investigated on the basis of analytical and numerical results. Comparisons are made with the results predicted by GL theory in the presence and absence of gravity for different values of time. Comparisons are also made between the three theories in the presence of rotation, gravity and in-homogeneity. Such problems are very important in many dynamical systems.

In recent years, the application of robots in different industrial sectors such as nuclear power generation, construction, automobile, firefighting and medicine, etc. is increasing day by day. In large industrial plants generally humans and robots work together to accomplish several tasks and lead to the problem of safety and reliability because any malfunction event of robots may cause human injury or even death. To access the reliability of a robot, sufficient amount of failure data is required which is sometimes very difficult to collect due to rare events of any robot failures. Also, different types of their failure pattern increase the difficulty which finally leads to the problem of uncertainty. To overcome these difficulties, this paper presents a case study by assessing fuzzy fault tree analysis (FFTA) to control robot-related accidents to provide safe working environment to human beings in any industrial plant.

Presented FFTA method uses different fuzzy membership functions to quantify different uncertainty factors and applies alpha-cut coupled weakest t-norm (Tω) based approximate fuzzy arithmetic operations to obtain fuzzy failure probability of robot-human interaction fault event which is the main contribution of the paper.

The result obtained from presented FFTA method is compared with other listing approaches. Critical basic events are also ranked using V-index for making suitable action plan to control robot-related accidents. Study indicates that the presented FFTA is a good alternative method to analyze fault in robot-human interaction for providing safe working environment in an industrial plant.

Existing fuzzy reliability assessment techniques designed for robots mainly use triangular fuzzy numbers (TFNs), triangle vague sets (TVS) or triangle intuitionistic fuzzy sets (IFS) to quantify data uncertainty. Present study overcomes this shortcoming and generalizes the idea of fuzzy reliability assessment for robots by adopting different IFS to control robot-related accidents to provide safe working environment to human. This is the main contribution of the paper.

The main goal of this paper is to develop novel Tω(weakest t-norm)-based fuzzy arithmetic operations to analyze the intuitionistic fuzzy reliability of Printed Circuit Board Assembly (PCBA) using fault tree.

The paper proposes a fuzzy fault tree analysis (FFTA) method for evaluating the intuitionistic fuzzy reliability of any nonrepairable system with uncertain information about failures of system components. This method uses a fault tree for modeling the failure phenomenon of the system, triangular intuitionistic fuzzy numbers (TIFNs) to determine data uncertainty, while novel arithmetic operations are adopted to determine the intuitionistic fuzzy reliability of a system under consideration. The proposed arithmetic operations employ Tω(weakest t-norm) to minimize the accumulating phenomenon of fuzziness, whereas the weighted arithmetic mean is employed to determine the membership as well as nonmembership degrees of the intuitionistic fuzzy failure possibility of the nonrepairable system. The usefulness of the proposed method has been illustrated by inspecting the intuitionistic fuzzy failure possibility of the PCBA and comparing the results with five other existing FFTA methods.

The results show that the proposed FFTA method effectively reduces the accumulating phenomenon of fuzziness and provides optimized degrees of membership and nonmembership for computed intuitionistic fuzzy reliability of a nonrepairable system.

The paper introduces Tω(weakest t-norm) and weighted arithmetic mean based operations for evaluating the intuitionistic fuzzy failure possibility of any nonrepairable system in an uncertain environment using a fault tree.

The purpose of this paper is to analyze the reliability of the washing system in a paper plant in a more promising way under vague environment by reducing the accumulating phenomenon of fuzziness and accelerating the computation process using the T_ω (weakest t-norm) based fuzzy lambda-tau (TBFLT) technique.

This paper presents a unified approach for analyzing the fuzzy reliability of the washing system under vague environment. This approach applies the TBFLT technique which uses triangular fuzzy numbers for incorporating data uncertainty, fault tree and lambda-tau method for finding system failure rate and repair time mathematical expressions while simplified T_ω-based arithmetic operations are applied for computing various reliability parameters of the system. The effectiveness of the TBFLT technique has been demonstrated by analyzing fuzzy reliability of the system using five different techniques including TBFLT. Moreover, this paper applies extended Tanaka’s (1983) approach to rank the critical components of the system.

The TBFLT technique has the advantage of low computation complexity in comparison to other techniques and effectively reduces the accumulating phenomenon of fuzziness. This main finding verifies the conclusion made by Chen (1994).

The author has suggested a simple and more applicable technique for analyzing the fuzzy reliability of any complex process industrial system under vague environment. The effectiveness of the technique has been demonstrated by computing various reliability parameters of the washing system of a paper plant.

An individual’s standard of living is profoundly affected by industrialization and technology’s continuous revolution. At present, the environment is uncontrollable and global warming is increasing. Therefore, there is a need to protect the earth immediately as the lives of all creatures are at risk. The purpose of this paper is to determine the factors related to green purchase behavior (GPB) by incorporating religious values (RGV) as a moderator. Moreover, the moderating role of RGV has been incorporated so that the importance of RGV in the life of millennials can be examined.

Smart partial least square (PLS) has been used for data analysis, and PLS-structural equation modeling has been used to assess measurement and structural models.

The findings reveal that environmental concern, environmental knowledge and green perceived value positively and significantly affect attitude and subjective norm (SN). Moreover, attitudes toward the purchase of green products and SNs also show a positive and significant relationship with green purchase intention (GPI). In addition, GPI is also positively and significantly associated with GPB. However, green brand knowledge portrays a positive but insignificant relationship with attitude and SN. Finally, RGV does not strengthen the relationship between intention and behavior.

Religion is a strong predictor of individual behavior as people are emotionally connected with Islam’s teachings. Therefore, the study provides a unique contribution by adding RGV as a moderator in the model of TRA. Also, the authors targeted the specific generation, i.e. millennials, so that millennials’ behavior can be identified as it covers Pakistan’s large population. Also, millennials are the people who are more involved in decision-making.

This review aims to synthesize the brand hate literature and suggest directions for future research on brand hate.

This study adopted an integrative literature review method to synthesize and assess the brand hate literature.

The synthesis showed that social identity theory, disidentification theory and duplex theory are prominently used in brand hate studies, and a larger portion of brand hate research was conducted in Western countries. Further, brand-related, self-congruity, personal factors, information influence and brand community influence are the major types of antecedents of brand hate which can produce soft or hard consequences. Lexicometric analysis showed causes of brand hate, consumers' negative emotional and behavioral outcomes and community anti-brand behavior as key themes of brand hate research.

The synthesis has followed predefined criteria for the inclusion research papers. Thus, the review is limited to articles that fulfilled the criteria for inclusion.

The finding will help marketers, specially brand managers, craft strategies to handle brand hate.

The brand hate literature is still developing and remains incoherent, suggesting that a synthesized review is needed. This study has systematically reviewed and synthesized the brand hate literature to study its development over time and proposes a framework which provides a comprehensive understanding of brand hate.

The research analyzes the influence of three environmental triggers, i.e. awareness, concern and knowledge on environmental attachment and green motivation that affect tourists' pro-environmental behavior in the Pakistan’s tourism industry. Furthermore, this study has analyzed the moderating role of moral obligation concerning environmental attachment and green motivation on tourists' pro-environmental behavior.

Data were gathered via a structured questionnaire by 237 local (domestic) tourists of Pakistan. Furthermore, the data were examined by employing SmartPLS.

Findings demonstrate that all three environmental triggers have a positive and significant relationship with environmental attachment and green motivation. Accordingly, environmental attachment and green motivation promote tourists' pro-environmental behavior. Furthermore, the moderating role of moral obligations has also been incorporated in the study. The finding reveals a strong and positive relationship among environmental attachment and tourists' pro-environmental behaviors during high moral obligations. In contrast, moral obligations do not moderate association between green motivation and tourists' pro-environmental behavior. Therefore, competent authorities should facilitate tourists to adopt environmentally friendly practices; which will ultimately promote pro-environmental behavior.

This study provides useful insights regarding the role of tourism in fostering environmental attachment and green motivation that sequentially influence tourist pro-environmental behavior. Secondly, this research has employed moral obligations as a moderator to identify the changes in tourists’ pro-environmental behavior based on individuals' ethical considerations. Hence, the study provides an in-depth insight into tourists' behavior. Lastly, the present research offers effective strategies for the tourism sector and other competent authorities to increase green activities that can embed the importance of the environment among individuals.

The study aims to inspect the impact of employees’ perception of corporate social responsibility (CSR) and their spiritual values on their affective commitment and job satisfaction, which in turn may promote organizational citizenship behavior. Furthermore, this study examines the moderating effect of Islamic work ethics to identify whether they strengthen or weaken the proposed associations.

A survey instrument was devised to collect data from employees. The statistical analysis of the data was conducted using the Smart PLS software. Additionally, the research uses the “Partial Least Square-Structural Equation Modelling (PLS-SEM)” technique.

The findings of the study suggest that employees’ perception of CSR exhibits a positive association with affective commitment and job satisfaction. Likewise, employees’ spiritual values demonstrate a positive and significant correlation with affective commitment and job satisfaction. Finally, the outcomes reveal that affective commitment and job satisfaction play a major role in fostering organizational citizenship behavior. Moreover, Islamic work ethics positively and significantly moderate the relationship between employee CSR perception and affective commitment and between employee CSR perception and job satisfaction.

This research study endeavors to fill the gaps in the current literature by investigating two crucial aspects of employees: their perception of CSR and spiritual values. Additionally, the study includes Islamic work ethics as a moderator to provide a more comprehensive understanding of how these factors contribute to fostering organizational citizenship behavior. This work highlights the significance of spiritual values and social responsibilities in employees’ lives and how Islamic work ethics shape their behavior accordingly.

The aim of this research study is to develop a queue assessment model to evaluate the inflow of walk-in outpatients in a busy public hospital of an emerging economy, in the absence of appointment systems, and construct a dynamic framework dedicated towards the practical implementation of the proposed model, for continuous monitoring of the queue system.

The current study utilizes data envelopment analysis (DEA) to develop a combined queuing–DEA model as applied to evaluate the wait times of patients, within different stages of the outpatients' department at the Combined Military Hospital (CMH) in Lahore, Pakistan, over a period of seven weeks (23rd April to 28th May 2014). The number of doctors/personnel and consultation time were considered as outputs, where consultation time was the non-discretionary output. The two inputs were wait time and length of queue. Additionally, VBA programming in Excel has been utilized to develop the dynamic framework for continuous queue monitoring.

The inadequate availability of personnel was observed as the critical issue for long wait times, along with overcrowding and variable arrival pattern of walk-in patients. The DEA model displayed the “required” number of personnel, corresponding to different wait times, indicating queue build-up.

The current study develops a queue evaluation model for a busy outpatients' department in a public hospital, where “all” patients are walk-in and no appointment systems. This model provides vital information in the form of “required” number of personnel which allows the administrators to control the queue pre-emptively minimizing wait times, with optimal yet dynamic staff allocation. Additionally, the dynamic framework specifically targets practical implementation in resource-poor public hospitals of emerging economies for continuous queue monitoring.

The purpose of this study was to develop a suitable module for digital conservation of traditional knowledge of medicinal plants (MPs) used by tribal communities living in the Anuppur district of Madhya Pradesh, Central India.

The research used a qualitative approach to gather the data of MPs through the use of literature review and field survey. Based on the acquired data, a prototype digital learning system was constructed and assessed. This study used digital learning technologies to assess the requirements for transmitting traditional knowledge of important MPs used by tribal communities so that people can absorb and conserve them.

Over time, the focus on the digital conservation of traditional MP’s knowledge has progressively increased globally. Despite the rise in this field of study, information technology methods to preserve and distribute traditional knowledge of MPs have remained a few. When adopting digital learning to maintain traditional knowledge of MPs, it was discovered that it would be necessary to engage with relevant knowledge keepers, use multimedia, and provide content in local languages.

This study helps in conservation of important MP species that are having biologically important therapeutic compounds meant for treating various ailments. Older generations of various tribal communities mainly hold traditional knowledge of important MPs, and unless it is preserved, it will perish along with its caretakers.

It is worth looking at a digital platform that can help future generations to maintain traditional knowledge of MPs, as it is a dynamic and ever-changing, it must involve a digital tool for its future conservation. Current methods for maintaining traditional knowledge of MPs were ineffective and constrained by space and time.