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Stress is the most common emotional or mental state that employees experience during their work. The employees in academics and industry are facing increased levels of stress as they progress through their work. The study aims to investigate the relationship between academic and industry employees’ stress personalities. West Coast psychological consultants Mary Dempcy and Rene Tihista distinguish between the seven various types of stress and offer suggestions to deal with it.

In this study, the authors have built a survey questionnaire using a sample of 195 respondents from the industry and academic of North India and analysed their responses to find their stress personalities at work. The Independent sample t-test approach has been applied to analyse the employee stress personality.

The study finds out that stress is a sophisticated defence mechanism that is unique to each individual and varies depending on the environment. Using employee response of academic and industry, the study covers the essence of seven types of stress for individuals, and that lent good support to the framed hypothesis.

These seven types of stress have importance and different levels to knowing their appropriateness to the individuals and suggest to take necessary action of plan. It shows the individuals feel about stress, how the bodies react to it and how to cope with it are all indicators of the personalities, attitudes and adaptability.

The novelty of this study is to apply Mary Dempcy and Rene Tihista’s stress personalities compared with the two respective categories.

The purpose of this paper is to propose distributed learning-based three different metaheuristic algorithms for the identification of nonlinear systems. The proposed algorithms are experimented in this study to address problems for which input data are available at different geographic locations. In addition, the models are tested for nonlinear systems with different noise conditions. In a nutshell, the suggested model aims to handle voluminous data with low communication overhead compared to traditional centralized processing methodologies.

Population-based evolutionary algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and cat swarm optimization (CSO) are implemented in a distributed form to address the system identification problem having distributed input data. Out of different distributed approaches mentioned in the literature, the study has considered incremental and diffusion strategies.

Performances of the proposed distributed learning-based algorithms are compared for different noise conditions. The experimental results indicate that CSO performs better compared to GA and PSO at all noise strengths with respect to accuracy and error convergence rate, but incremental CSO is slightly superior to diffusion CSO.

This paper employs evolutionary algorithms using distributed learning strategies and applies these algorithms for the identification of unknown systems. Very few existing studies have been reported in which these distributed learning strategies are experimented for the parameter estimation task.

Human resource management, Training and development, Competency development and team spirit.

The case is intended for MBA/PGDM level students as part of a human resource management curriculum. The case is more diagnostic in nature and should be discussed in the same spirit. The case is suitable for developing conceptual thinking and community orientation of professionals aspiring or pursuing a career in the area of human resource management.

The case examines the imperatives behind Sterling Tools Limited (STL), a leading fasteners manufacturing Indian company's decision and strategy adopted to inculcate team spirit through outdoor experiential training (OET). The case explores in detail the process undertaken to execute the OET at STL. The case also briefly mentions the tangible benefits of OEL. The case is structured to enable readers to: understand the basic objectives of OET; understand the innovative approach adopted by STL; and understand how an organization responds to changes and challenges in the external environment.

This case is structured to enable students to: understand the meaning and significance of outdoor experiential training (OET); analyze the challenges faced by HR managers in modern day organizations; learn the conceptual framework and understand the principles of OET; examine the measures that can be taken by management to ensure a smooth induction and socialization process of employees; and understand the need of inculcating team spirit among employees.

Teaching notes are available.

Present research analyzes and evaluates the impact of e-resources usage factors (training modes, awareness, influencers, utilitarian benefits and ease of use) towards satisfaction and intention to use these e-resources.

The data for present study were collected from postgraduate students of Delhi (India) and 248 valid responses were received through the survey. After reliability and validity tests, structural relationships between variables were studied.

The present study revealed that all five factors significantly affected satisfaction and intention to use e-resources. However, influencers were found to have the highest impact on satisfaction and intention to use e-resources.

The present study is a maiden attempt to explore the impact of e-resources usage factors on satisfaction and intention to use by postgraduate students at management schools in Delhi, India.

The purpose of this paper is to analyse service quality in the automobile maintenance and repair industry. A conceptual structural model is developed to investigate the impact of service quality, perceived service fairness and convenience on customer service satisfaction. The impact of service satisfaction and brand trust on word of mouth (WOM) is also explored, and the study assesses the mediating effect of customer service satisfaction on the relationship between service quality and WOM.

Data from a questionnaire-based survey of 259 users of automobile maintenance and repair centres were analysed using covariance-based structural equation modelling.

The findings indicate that service quality dimensions (reliability, responsiveness and empathy), perceived service fairness and convenience are positively associated with customer service satisfaction, and that service satisfaction and trust positively influence WOM. The findings support the mediating effect of service satisfaction on the relationship between reliability and responsiveness and WOM.

The study’s main limitation is the cross-sectional design, which limits the generalisability of the findings.

To ensure customer satisfaction and generate trust and WOM, automobile maintenance and repair service centres should improve reliability, responsiveness and empathy, as well as perceived service fairness and convenience.

The study demonstrates that the reliability and responsiveness dimensions of service quality are the most significant predictors of customer service satisfaction in the automobile maintenance and repair industry.

Health care organisations implement lean six sigma (LSS) methodology to achieve improved performance in terms of cost, quality and productivity. However, the way it gets implemented differs between organisations. Hence, this paper deal with a review of case studies describing the implementation of LSS in health care organisations to understand the nuances of implementation and identify future research directions.

The journal articles indexed in the Web of Science and Scopus database were filtered out. In total, 154 articles were evaluated using specific structural dimensions to categorise the literature into various groups, and content analysis was performed to synthesise the same.

This review revealed that the number of articles publishing the application of LSS in health care has been increasing in the last five years. Academic hospitals play a pivotal role to bridge the gap between LSS theory and practice. Despite this fact, certain themes remain unexplored. Not many studies are available that document the application of LSS in non-clinical areas such as pharmacy, internal logistics, maintenance and medical records. Only 20% of articles mentioned the post-intervention data up to three years, thus questioning the sustainability aspect of the achieved improvements.

Various research gaps were identified, which can be used by the researchers to build the body of knowledge in the domain of LSS in health care.

This review provides a diversified view regarding the utility of LSS in the health care scenario. The findings will provide valuable insights for the health care practitioners regarding tools, techniques, drivers and performance measures.

To the best of the authors’ knowledge, this is the first study to review only the case studies that describe the implementation of LSS in the health care sector.

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.

This paper aims to assess the relationship between academic burnout-student engagement relationships on management students of the Delhi-NCR region of Northern India. It further attempts to study the moderating impact of internal locus of control and mediating impact of loneliness on the academic burnout-student engagement relationship.

The data was collected using standardized instruments from 264 respondents. Descriptive statistics, correlation and moderated-mediated regression analysis were used to test the hypotheses.

The study found a negative association between student engagement and academic burnout and loneliness. A positive association between academic burnout and loneliness and a moderating impact of internal locus of control on academic burnout and student engagement relationship. Loneliness acted as a partial mediator for the moderated relationship between the academic burnout-student engagement relationship.

Sample size and sampling units are the limitations of the study.

The conclusion of the presented study offers different inferences including validating the self-determination theory (Ryan and Deci, 2000) and possible courses of actions to be taken by academic institutions and students themselves. It ranges from careful investigation of student’s behaviors, design and implements collaborative projects along with student’s involvement in social networking based groups for collaborations and help.

With the help of the study, the society including parents, family, friends, officials and academicians at educational institutions can offer useful insights to students through recreational and social activities for behavior modifications.

The major contribution of the study is to understand the psyche of the budding professionals perceiving increased stress and pressure. Limited studies are found in the Indian context and no studies in the past have used the study variables together. Internal locus of control as a personality variable has not been studied with respect to student’s burnout and engagement. Furthermore, none of the studies done in the past have deliberated upon loneliness with respect to the student community.

A low power flip-flop circuit is designed for energy-efficient devices. Digital sequential circuits are in huge demand because every processor has most of the parts of digital circuit. The sequential circuits consist of a basic data storing element, a latch is used to store single bit data. The flip-flop takes a sufficient portion of the total chip area and overall power consumption as well. This study aims to the low power energy-efficient applications like laptops, mobile phones and palmtops.

This paper proposes a new type of flip-flop that consists of the only 16 transistors with a single-phase clock. The flip-flop has two blocks, master and slave latch. In this design, the authors have focused on only master latch, which includes a level restoring circuit. It is used to help the master latch in data retention process. The latch circuit has two inverters in back-to-back arrangement. The proposed flip-flop is implemented on 65 nm complementary metal oxide semiconductor technology using Cadence Virtuoso environment and compared with other reported flip-flops.

The proposed flip-flop architecture outperformed the peak percentage, i.e. 79.25% as compared to transmission gate flip-flop and a minimum of 20.02% compared to 18 T true single phase clocking (TSPC) improvement in terms of power. It also improved C to Q delay and power delay product. In addition, by reducing the number of transistors the total area of the proposed flip-flop is reduced by a minimum of 13.76% with respect to 18TSPC and existing flip-flop. For reliability checking the Monte Carlo simulation is performed for thousand samples and it is compared with the recently reported 18TSPC flip-flop.

This work is tested by using a test circuit with a load capacitor of 0.2 fF. The proposed work uses a new topology to work as master-slave. Power consumption of this technique is very less and it is best suitable for low power applications. This circuit is working properly up to 2 GHz frequency.

Many healthcare institutions, such as hospitals, have recently implemented quality improvement initiatives such as Lean Six Sigma (LSS). However, only a few have sustained the initiatives and remained successful. One of the main reasons for the failure of LSS implementation is that managers tend to view LSS as individual projects. Managers lack a Change Management (CM) focus during the implementation. The primary purpose of this study is to document the implementation of LSS through a CM approach to improve sustainability.

Define-Measure-Analyse-Improve-Control (DMAIC) and the Awareness-Desire-Knowledge-Ability-Reinforcement (ADKAR), a popular CM approach, are combined to propose a new framework. The usefulness of the proposed framework is demonstrated using a case study in a multispeciality hospital located in southern India.

The study found that several factors are responsible for the high Length of Stay (LOS) for patients in the Emergency Department (ED). By implementing this proposed model to implement LSS and taking corrective actions, the average LOS was reduced from 267 to 158 min (a 40% reduction approximately).

The complete step-by-step approach is explained, and the LOS was considerably reduced during the pilot project. The findings will provide valuable insights for healthcare practitioners to understand the steps involved in the combined DMAIC-ADKAR model. The findings would also give healthcare practitioners the confidence to identify suitable tools and implement LSS in organisations where the practitioners work.

According to the authors' knowledge, this is the first study that synergises two models (DMAIC and ADKAR) into a single framework to implement in a hospital.