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The purpose of this paper is to understand the effect of engine operating conditions and lubricant friction modifier on direct acting tappet rotation. In this research work, novel method of measuring engine tappet rotation speed has been developed. The technique is so novel. It allows the measurement on real production engine with no modification to the engine tappet bore. Also, In this paper, the effect of engine operating conditions and the effectiveness of friction modifier on tappet rotation is reported.

For the very first time, for the purpose of measuring follower rotation in a real production engine, a 4 × 6 mm2 electronic chip called Gradiometer is mounted outside the tappet housing, allowing the monitoring of tappet rotation speed without the need to machine a hole in the tappet bore. This novel technique is adopted on Mercedes Benz OM464 engine to study the effect of engine conditions and lubricant chemistry on tappet performance.

The main outcome of this research work is the development of novel method of measuring tappet rotation. Also, during the experiments, it was revealed that although friction modifiers help in reducing friction at the cam/tappet interface, they can also adversely affect the tappet rotation speed.

The novel technique developed in the research work is one of the most cost effective and simple to use. Researches can adopt the technique to study the tribological performance of direct acting tappet on real production engine. Researches acknowledge the effectiveness of friction modifiers in valve train but its effect on rotation which plays a key role in the component durability has not been the focus of most of the researches mainly due to lack of effective techniques.

The purpose of this paper is to elucidate the social information processing theory, which is extended by the (1) effect of whistleblowing education on whistleblowing intentions, (2) simultaneous examination of the indirect relationship between whistleblowing education and whistleblowing intentions via moral identity and (3) relativism in influencing this mediation.

Multi-wave data collected at three internals from bank employees (n = 294) were analyzed to test the proposed model.

Results of the study demonstrate that whistleblowing education favorably influences whistleblowing intentions directly as well as through moral identity. Relativism serves as the buffer in the indirect effects of whistleblowing education on whistleblowing intentions through moral identity attenuating these indirect effects in individuals with dominant relativism level.

This study strives to extend the whistleblowing education and whistleblowing intentions literature by unpacking a moral identity mechanism through which whistleblowing education kindles whistleblowing intention and relativism as boundary condition to attenuate such motivation.

The purpose of this study is to explore the potential impact of Industry 5.0 on businesses and management by integrating advanced technologies to develop smart cities (Society 5.0) and digital value chains, leading to Innovation 5.0 and triple bottom line sustainability. We propose an Organization Value Chain 5.0 model to describe the ecosystem interactions that leverage organizational innovative behavior through knowledge management.

Using a systematic literature review methodology, we conducted a comprehensive analysis of 968 Industry 5.0 articles, 297 Innovation 5.0 articles and 510 Society 5.0 articles from the WOS and Scopus databases. This analysis supports the development of our conceptual model.

This allowed us to propose the conceptual model for the new notion of Organization Value Chain 5.0 and its ecosystem components.

This study provides a detailed analysis of Industry 5.0, its technological elements and its relevance to creating Society 5.0, smart cities and digitalized value chains. It highlights the importance of stakeholder engagement and integration for effective digital industrial transformation.

This study aims to examine the impact of terrorism on return and systematic risk of Pakistan’s equity industries. Daily data from 1 January 2000 to 31 December 2014 for 12 industries based on the specific types of companies listed on Karachi Stock Exchange are used for the empirical analysis.

A multiplicative (additive) term is introduced in the standard capital asset pricing model to examine the change in systematic risk (industry returns) in response to the terrorist activities. The authors use the multiscale beta approach (Yamada, 2005) and the maximal overlap discrete wavelet transform (MODWT) to test the heterogeneous market hypothesis.

Terrorism activities increase the systematic risk for most of the industries and the negative impact on returns of banks and the financial industry. It is noted that terrorism positively impacts (increases) the industrial systematic risk mainly in short-run (between two and four days-time horizon).

The paper examines the impact of terrorism on a broad list of industries’ (banks, basic materials, chemicals, construction, consumer goods, consumer services, financials, industrials, minerals, oil and gas, textile and utilities) risk and return in Pakistan, using the multiscale beta approach (Yamada, 2005) and the MODWT methods.

This article aims to highlight the stigmatization attached to the unemployment of educated youth in rural regions of Khyber Pakhtunkhwa province of Pakistan.

The study explicates the subjective experiences of the youth as being unemployed and societal attitudes toward them through an in-depth qualitative approach. A total of 30 unemployed male individuals were interviewed through an interview guide.

The study reveals that unemployed individuals are stigmatized and discriminately treated. They experience the difference in social support from their family and friends during unemployment, which is a discouraging aspect. This finding is in contrast to the existing literature on the subject in which family and friends are described as a major source of social support. As the study is conducted in the rural context, it is observed that local factors coupled with the joint family system have intensified negative attitudes toward the unemployed youth. Subsequently, the negative societal treatment serves as a factor for psychological challenges in their lives.

This article serves the need of exploring the experiences of unemployed individuals precisely in the Pakistani context.

Many construction projects exhibit poor performance in terms of fulfilling predetermined schedules and financial objectives. Project control systems (PCSs) have been used to enhance construction project performance; however, a comprehensive framework regarding the key determinants of PCS effectiveness is lacking.

Herein, the determinants for effective PCSs that can improve construction project performance were comprehensively identified by evaluating existing studies. A systematic strategy following the preferred reporting items for systematic reviews and meta-analyses protocol was employed to search for and select relevant studies, followed by a qualitative synthesis.

The significance of incorporating and managing many factors associated with PCS for effective project delivery was elucidated. The study synthesized 12 key determinants and 29 sub-determinants of PCS effectiveness in project delivery and grouped them into organizational, human, technological and operational categories. Out of the four categories examined, operational aspects received the most references, underscoring their critical role in PCS effectiveness, while human-related dimensions received the least amount of attention in the reviewed research, accounting for 4%. This also revealed a significant gap in the research addressing the interactions between all PCS aspects.

Understanding of the variables influencing PCS effectiveness in construction project delivery was enhanced, and a framework for future PCS research in five dominant areas was created.

Drawing upon Drucker’s theory of productivity, this study proposes to examine the relationship between knowledge-oriented leadership (KOL) and knowledge worker performance (KWP) within the Chinese information technology (IT) industry during the COVID-19 pandemic. Further, this study examines the direct connection between KWP and organizational performance (OP), as well as mediated via employee creative work behavior (ECWB), and digital citizenship behavior (DCB).

The data for the research was collected from a sample size of 322 individuals working in the IT industry context in China, with varying levels of seniority (lower, middle and upper). The relationship was examined by employing Smart PLS 4 in a current study.

The study findings revealed a significant and conspicuous effect of KOL on KWP. The outcomes divulged the fact that KOL has a positive impact on the ECWB, and DCB improves the performance of knowledge workers, resulting in an overall augmentation in the organizational performance of the IT industry.

Presently, there exist a scarcity of substantial empirical studies to thoroughly examine the influence of KOL, ECWB, DCB, KWP and OP in the domain of Chinese IT industry research, particularly in the setting of the pandemic. The study makes a substantial contribution to the extant literature on the topic via empirically examining the association among KOL, KWP and organizational performance, as well as evaluating the mediation mechanism of both employee creative work behavior and digital citizenship behavior.

Perception of organizational politics is one of the key factors of the organization's performance. Based on the principles of Game Theory, this study aims to examine the impact of management's and employee's politics within an organization on the psychological and organizational stress levels of workers, followed by their task and contextual performance.

Following the non-probability convenience sampling technique, the data was collected from the managerial and non-managerial staff of public, private and semi-government services organizations in Rawalpindi, Islamabad, Lahore, Faisalabad, Gujranwala, Abbottabad and Karachi cities in Pakistan.

The structural analyses indicate that organizational politics is a major cause of stress among workers and has a significant positive impact on the psychological and organizational stress of workers. Moreover, both organizational politics and job stress hinder workers' performance.

The findings of the current research provide valuable insights into the management of firms about the destructive role of politics with a special focus on psychological and organizational stress, followed by job and contextual performance, particularly in the context of Pakistan. It also proposes strategies to counter this issue, improving worker's performance. Furthermore, the findings also suggest whether management or employees are more involved in organizational politics.

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

This study investigates how the initiatives and controversies related to environmental, social and governance (ESG) explain firm efficiency.

Firstly, this study applies data envelopment analysis with the epsilon-based measure to estimate the firm efficiency of 80 companies in the Chinese energy sector in 2022. This approach accounts for the diversity and relative importance of inputs and outputs from a multidimensional perspective. Secondly, this study regresses the variables of ESG initiatives and controversies on the estimated firm efficiency scores through a generalised additive model, which can capture nonlinear patterns.

This study finds that a) the samples have i) about 49% room for improvement in efficiently optimising their resources and business outcomes and ii) the highest scores in governance initiatives, followed by social initiative. b) 69% of them have controversy scores that are greater than the average value. c) A cluster analysis indicates that companies with higher social initiatives have higher firm efficiency than their counterparts. d) ESG initiatives and controversies are nonlinearly related to firm efficiency.

The findings have practical implications for policy makers and managers who prioritise ESG, particularly regarding (i) the need to examine firm performance from a multidimensional perspective, that is, to measure multiple inputs and outputs simultaneously, (ii) the nonlinearity of the nexus between ESG and efficiency in graphical forms, and (iii) the need to balance ESG initiatives and address ESG controversies.

This study integrates statistical approaches in examining and ensuring sustainable growth and efficiency within the Chinese energy sector and beyond.