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Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

The increasing adverse impact of human behavior toward the environment has brought in changes in research focus on environmental behavior toward the workplace. Because the employee spends one-third of his day in his workplace, the initiatives taken by the employee also have an impact on the company’s environmental stance. Therefore, the researchers gradually focus on employee green behavior (EGB) and its measurement. The study aims to devise a tool for measuring EGB.

Two studies were carried out using the survey method using the purposive sampling technique. The data were collected (Studies 1 and 2) from managers and supervisors working in manufacturing companies located in Kolkata, India.

The first study was done to extract the principal factors using an initial 30 items (N = 220). The result of the principal component analysis shows the emergence of three factors spread over 20 items with loadings above 0.40. The 20-item scale was again administered on managers and supervisors (N = 243). The second study was carried out to examine the convergent and discriminant validity as well as stability of the tool through confirmatory factor analysis (CFA) (N = 243). The result of CFA showed the presence of 16 items spread through three factors: practice and policy, digital use and recycle and reuse. Multiple fit indices support a three-factor model of the 16-item EGB scale.

The scale would be a good measure of EGB and can be used for further research. The EGB scale is a composite scale containing three major dimensions that can be used as a complete measure of EGB.

The present research aims to fill the current gap by building a comprehensive tool for measuring EGB. The present scale has also addressed the shortcoming of the previous scale and tried to include varied proenvironmental behaviors exhibited in the workplace.

The purpose of this study is to ensure the successful implementation of a landing cushion for the new generation armored vehicles with significantly enhanced quality. Furthermore, to introduce a high-precision landing cushioning analysis model.

To accurately analyze the cushioning performance of the new generation armored vehicles, a nonlinear finite element dynamics model considering the complex travel system was established. The model considered the influence of various nonlinear factors to measure the dynamic response difference between the proposed and traditional models. The cushioning performance of airbags under different landing conditions and their various influence factors were analyzed.

The travel system has a large influence on the key points of the vehicle, whose rear end of the upper deck has a larger acceleration fluctuation compared with the traditional model. The increase in the body material stiffness is helpful to reduce this fluctuation. The established nonlinear finite element model can effectively analyze the landing cushioning performance of airborne armored vehicles. The area of the external airbag vent has a large influence on the cushioning performance, and the cushioning system has excellent cushioning performance under various operating conditions.

This study introduces the travel system, which is ignored by traditional analytical models. The interactions between various types of complex structures are included in the analysis process in its entirety, leading to valuable new conclusions. Quantitatively reveals the analytical errors of traditional simulation models in multiple dimensions and the reasons for their formation. Based on a high-precision simulation model, it is verified that the designed airbag cushioning system has an excellent cushioning effect for the new generation of heavy airborne armored vehicles.

The novelty of this work comes from the need for smooth landing with low overload for a new type of large-load airborne armored vehicle and provides a high-precision model that quantifies the traditional analytical modeling errors and error principle.

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

This study aims to investigate the situational factors that intensify the impact of leader bottom-line mentality (BLM) on employee pro-self-unethical behavior. In particular, the moderating role of contingent rewards and punishments is evaluated under the lens of situational strength theory.

Data were collected from 218 full-time employees working in the USA in a time-lagged study and analyzed using SPSS Process Macro.

Statistical analysis reveal contingent rewards and punishments significantly moderate the positive relationship between BLM and pro-self-unethical behavior.

This paper highlights the need for more balanced reward systems that incorporate moral conduct into work performance. It also emphasizes the role of robust accountability and monitoring systems in minimizing employees’ unethical behavior.

To the best of the authors’ knowledge, this is the first study to investigate the moderating role of contingent rewards and punishments on the relationship between leader BLM and subordinate pro-self-unethical behavior. Moreover, it provides significant empirical support to situational strength theory.

The COVID-19 pandemic brought uncertain working patterns in a volatile, uncertain, complex and ambiguous world wherein unleashing power of knowledge became prototypical for real-time decision-making capacity of organizational workforce. Drawing from Vroom’s expectancy theory, this study aims to investigate whether shared leadership (SL) mediates the impact of perceived fairness of rewards (PFR) on knowledge capitalization (KC).

A survey of 484 employees in the Indian real estate industry was completed in two phases. Confirmatory factor analysis and structured equation model were applied for analysis and hypothesis testing.

PFR positively affected employee’s KC in Indian real estate industry. Also, SL partially mediated the effect of PFR on KC.

This study indicates the positive impact of PFR on employees’ KC and demonstrates position of SL for boosting its occurrence in organizations.

To the best of the authors’ knowledge, this paper is the first to investigate the mediating role of SL between relationship of PFR and KC of employees.

This paper aims to examine the mediation effect of organizational learning on the link between human resource management (HRM) practices and organizational performance in some Big4 financial services companies.

The quantitative methodology was chosen for this research, using resource theory and knowledge-based approach to explain the relationship between latent variables. A sample of 403 HR employees and managers of the companies under study in France was selected in 2022. Structural equations modeling was used based on the Spss-Amos program to test the research hypotheses.

The results revealed that organizational learning played a mediating role between HRM practices (hiring, training, motivation and decision-making) and organizational performance and that learning enabled the performance of workers to improve and achieve competitive advantages in this field.

The sample was based on four international companies working in the field of financial services and consulting and providing their services within France, which may affect the generalisability of the results and limit them to the studied sector.

The contribution of the study is to improve the awareness of administrators, decision makers and company employees of the importance of organizational learning for companies, and to stimulate motivation to learn and exchange knowledge in a constructive way that enhances organizational performance. Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

This study seeks to provide cadres and executives with an in-depth analysis of HRM and organizational learning, which, through its integration of these attributes, can contribute to the earning of knowledge-based competitive advantage and achieve superior and sustainable performance.

This paper aims to focus on the issue of high employee turnover in the Indian tech industry. An integrative review is conducted to analyse the past and current state of literature, as well as prepare a research agenda for future studies.

A pool of 72 articles published between 2010 and 2022 is reviewed with a special focus on Indian tech employees. This study elucidates the extent and impact of employee retention strategies through content analysis.

Two broad perspectives have been established in the literature: the reasons for quitting and the explanations for staying. By means of a comprehensive review, this paper combines these two aspects of literature and suggests factors under organization’s control to retain competent tech employees.

The study is designed to integrate the two theoretical viewpoints of employee turnover literature by consolidating the reasons behind quitting behaviour and staying intention. Codes combining the two aspects are presented as a valuable resource to retain tech talent.

The purpose of the present study was to identify the conditions that affect the absorptive capacity (AC) of knowledge, discover its consequences and design an AC paradigm pattern in public academic libraries. To do so, AC was investigated at the levels of individual and organizational learning.

In this paper, to answer the three major questions of this qualitative-survey study, the views of 24 experts were examined using an in-depth semi-structured interview and grounded theory strategy. The data were collected using a nonrandom combined targeted sampling procedure (targeted and snowball) and analyzed based on Strauss and Corbin’s (1998) approach and utilizing MAX Qualitative Data Analysis (MAXQDA) software.

Throughout the grounded analytic stages, 121 open codes were identified. These were distributed around the AC axial category in academic libraries in terms of individual and organizational learning. The 33 axial concepts were then categorized into 16 selective general categories. The paradigm pattern was initially designed to explore the relationships between causal, intervening, strategies, context and consequences conditions. The transition from academic libraries to learning organizations, their increased functional value and the development of their innovation were identified as the consequences of AC development.

This qualitative research is the first in the field of Library and Information Science (LIS) to support AC both theoretically and empirically in terms of learning in academic libraries. This study thus not only addresses a key research gap in LIS but also provides significant insights and direction to interested librarians and researchers.

This study aims to better understand the morphological characteristics of single particle and the health risk characteristics of heavy metals in PM_2.5 in different functional areas of Handan City.

High resolution transmission electron microscopy was used to observe the aerosol samples collected from different functional areas of Handan City. The morphology and size distribution of the particles collected on hazy and clear days were compared. The health risk evaluation model was applied to evaluate the hazardous effects of particles on human health in different functional areas on hazy days.

The results show that the particulate matter in different functional areas is dominated by spherical particles in different weather conditions. In particular, the proportion of spherical particles exceeds 70% on the haze day, and the percentage of soot aggregates increases significantly on the clear day. The percentage of each type of particle in the teaching and living areas varied less under different weather conditions. Except for the industrial area, the size distribution of each type of particle in haze samples is larger than that on the clear day. Spherical particles contribute more to the small particle size segment. Soot aggregate and other shaped particles contribute more to the large size segment. The mass concentrations of hazardous elements (HEs) in PM_2.5 in different functional areas on consecutive haze pollution days were illustrated as industrial area > traffic area > living area > teaching area. Compared with the other functional areas, the teaching area had the lowest noncarcinogenic risk of HEs. The lifetime carcinogenic risk values of Cr and As elements in each functional area have exceeded residents’ threshold levels and are at high risk of carcinogenicity. Among the four functional areas, the industrial area has the highest carcinogenic and noncarcinogenic risks. But the effects of HEs on human health in the other functional areas should also be taken seriously and continuously controlled.

The significance of the study is to further understand the morphological characteristics of single particles and the health risks of heavy metals in different functional areas of Handan City. the authors hope to provide a reference for other coal-burning industrial cities to develop plans to improve air quality and human respiratory health.