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We examine the relationships among leader spirituality, organizational innovativeness, transformational leadership style and project success. Integrating principles of behavioral learning and social learning theories, we argue that spiritual leadership style is positively linked to project success, and this relationship is mediated by transformational leadership. Furthermore, the relationship between leader spirituality and transformational leadership is moderated by organizational innovativeness.

Data are collected from 180 individuals working in seven large project-based organizations from the telecom sector in Pakistan. The individuals comprise engineers, functional managers, dedicated project managers and individuals who have led and/or worked in project teams. Data are analyzed using variance-based structural equation modeling.

Results suggest that the relationship between spiritual leadership style and project success is positive and is partially mediated by transformational leadership. Furthermore, organizational innovativeness positively moderates the spiritual leadership and transformational leadership relationship.

Research calls for examining the relationship between leadership styles and project success. We address this call through examining the role of spiritual leadership style (which is rather ignored in project management literature) for project success. Furthermore, we take a novel evolutionary approach of integrating different leadership styles and indicating determinants as well as contingencies to leadership development.

The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with multiple gateways. It entails IoMT devices and wearables connecting to exchange sensitive data with a sensor node which performs the aggeration process and then communicates the data using a Fog server. If the aggregator sensor loses the connection from the Fog server, it will be unable to submit data directly to the Fog server. The node transmits encrypted information with a neighboring sensor and sends it to the Fog server integrated with federated learning, which encrypts data to the existing data. The fog server performs the operations on the measured data, and the values are stored in the local storage area and later it is updated to the cloud server.

SHDCT uses an Internet-of-things (IoT)-based monitoring network, making it possible for smart devices to connect and interact with each other. The main purpose of the monitoring network has been in the collection of biological data and additional information from mobile devices to the patients. The monitoring network is composed of three different types of smart devices that is at the heart of the IoT.

It has been addressed in this work how to design an architecture for safe data aggregation in heterogeneous IoT-federated learning-enabled wireless sensor networks (WSNs), which makes use of basic encoding and data aggregation methods to achieve this. The authors suggest that the small gateway node (SGN) captures all of the sensed data from the SD and uses a simple, lightweight encoding scheme and cryptographic techniques to convey the data to the gateway node (GWN). The GWN gets all of the medical data from SGN and ensures that the data is accurate and up to date. If the data obtained is trustworthy, then the medical data should be aggregated and sent to the Fog server for further processing. The Java programming language simulates and analyzes the proposed SHDCT model for deployment and message initiation. When comparing the SHDCT scheme to the SPPDA and electrohydrodynamic atomisation (EHDA) schemes, the results show that the SHDCT method performs significantly better. When compared with the SPPDA and EHDA schemes, the suggested SHDCT plan necessitates a lower communication cost. In comparison to EHDA and SPPDA, SHDCT achieves 4.72% and 13.59% less, respectively. When compared to other transmission techniques, SHDCT has a higher transmission ratio. When compared with EHDA and SPPDA, SHDCT achieves 8.47% and 24.41% higher transmission ratios, respectively. When compared with other ways it uses less electricity. When compared with EHDA and SPPDA, SHDCT achieves 5.85% and 18.86% greater residual energy, respectively.

In the health care sector, a series of interconnected medical devices collect data using IoT networks in the health care domain. Preventive, predictive, personalized and participatory care is becoming increasingly popular in the health care sector. Safe data collection and transfer to a centralized server is a challenging scenario. This study presents a mechanism for SHDCT. The mechanism consists of Smart healthcare IoT devices working on federated learning that link up with one another to exchange health data. Health data is sensitive and needs to be exchanged securely and efficiently. In the mechanism, the sensing devices send data to a SGN. This SGN uses a lightweight encoding scheme and performs cryptography techniques to communicate the data with the GWN. The GWN gets all the health data from the SGN and makes it possible to confirm that the data is validated. If the received data is reliable, then aggregate the medical data and transmit it to the Fog server for further process. The performance parameters are compared with the other systems in terms of communication costs, transmission ratio and energy use.

This paper aims to design a PD controller for an active suspension system to improve the car’s moving smoothness.

The controller parameters are optimized by an in-loop genetic algorithm (iL-GA). Unlike previous studies that only used conventional GAs to tune coefficients for the controller, the iL-GA designed in this paper provides outstanding efficiency when determining the optimal value range for the system. The optimal value range of parameters is determined by the in-loop algorithm based on criteria related to systematic errors. The optimal values are then calculated by the GA based on this range instead of an uncertain one.

Simulation results show that vehicle body acceleration and displacement values are significantly reduced when using the active suspension system compared to the conventional passive suspension system. The phase difference phenomenon does not occur in the iL-GA situation. In addition, the frequency domain investigation also shows the system’s stability when using iL-GA instead of conventional GA.

To the best of the authors’ knowledge, this is a new application that provides positive effects to the suspension controller. This algorithm can be applied to tune coefficients for direct controllers in the future.

From a knowledge-management perspective, this paper aims to analyze the digital transformation of the business models of traditional Chinese sporting goods companies in the context of the pandemic crisis and to explore the role of their digital transformation in coping with the crisis.

Using theoretical sampling, typical sporting goods companies are selected for case studies. We provide an in-depth analysis of how these companies achieve high performance levels through the digital transformation of their business models in the post-COVID-19 era and discuss the key role of knowledge management in this achievement.

Focusing on the challenges faced by Chinese sporting goods enterprises during the pandemic crisis from the knowledge-management perspective, we find that through the digital transformation of their business models, enterprises can improve their knowledge-management capabilities, enhance their flexibility to respond to sudden crises and maintain a higher level of corporate performance.

This paper has significant implications for sporting goods companies wishing to achieve high corporate performance through the digital transformation of their business models in the post-COVID-19 era. Future research should address the dynamic mechanism of the digital transformation of business models to improve enterprise knowledge-management capabilities and the impact mechanism of knowledge-management capabilities on interenterprise organizational resilience.

This paper proposes specific strategies in the process of the digital transformation of business models that are essential for improving enterprises’ internal and external knowledge-management capabilities.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

Drawing on bargaining power and the inequality aversion perspective, this study aims to probe employees’ influence on addressing income inequality between top executives and nonexecutive employees. Meanwhile, it examines the moderating role of employee-related factors and plan attributes.

This study uses a staggered difference-in-differences design with a propensity scoring match approach and verification of the parallel trend assumption to test the hypotheses.

The results support the hypothesis that employee stock ownership plans (ESOPs) significantly reduce within-firm income inequality. The negative effect is amplified by both the presence of trade unions and the unemployment rate at the regional level, as well as the duration of the lock-in period and the scale of participants within the stock ownership plan.

This study has implications for income inequality research and ESOP design and provides theoretical support for policymakers and corporate governance.

This study contributes to the literature on income inequality by examining the implementation of ESOPs from the employee perspective. Furthermore, it extends the current literature by investigating the strengthening effects of regional factors and ESOP attributes on the relationship between ESOPs and income inequality. The conclusions provide new empirical evidence to promote the effective implementation of ESOPs by combining internal and external factors.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

To clarify divergent conclusions on the impact of alliances on green innovation (GI), this study aims to examine the non-linear relationships between dual alliance and GI, as well as the mediation of green knowledge reconstruction (GKR) and the moderation of alliance tie strength.

Based on the theory of knowledge-based view, a moderated intermediary model is constructed by introducing GKR and alliance tie strength. The hypotheses are validated by using hierarchical regression analysis and bootstrapping method, with questionnaire survey data collected from 316 manufacturing firms in China.

Empirical results show that both exploratory alliance and exploitative alliance have an inverted U-shaped effect on GI, in which GKR plays a mediating role in the above relationship. Moreover, alliance tie strength weakens the intermediary role of GKR in the relationship between exploratory alliance and GI, whereas it enhances the intermediary role of GKR in the relationship between exploitative alliance and GI.

Findings reveal the non-linear effects of dual alliance on GI and clarify the inconsistent conclusions by proposing the moderated intermediary effect model. Moreover, this research reveals the mechanism of dual alliance on GI through the mediation of GKR and enriches the boundary conditions by integrating the moderating role of alliance tie strength.

A wealth of studies have identified numerous antecedents to online self-disclosure. However, the number of competing theoretical perspectives and inconsistent findings have hampered efforts to obtain a clear understanding of what truly influences online self-disclosure. To address this gap, this study draws on the antecedent-privacy concern-outcome (APCO) framework in a one-stage meta-analytical structural equation modeling (one-stage MASEM) study to test a nomological online self-disclosure model that assesses the factors affecting online self-disclosure.

Using the one-stage MASEM technique, this study conducts a meta-analysis of online self-disclosure literature that comprises 130 independent samples extracted from 110 articles reported by 53,024 individuals.

The results reveal that trust, privacy concern, privacy risk and privacy benefit are the important antecedents of online self-disclosure. Privacy concern can be influenced by general privacy concern, privacy experience and privacy control. Furthermore, moderator analysis indicates that technology type has moderating effects on the links between online self-disclosure and some of its drivers.

First, with the guidance of the APCO framework, this study provides a comprehensive framework that connects the most relevant antecedents underlying online self-disclosure using one-stage MASEM. Second, this study identifies the contextual factors that influence the effectiveness of the antecedents of online self-disclosure.

By using Technology Acceptance Model, the purpose of this study is to investigate how the perceived usefulness and ease-of-use of shopping mobile apps affects consumer’s flow experience, attitude, impulsive buying tendency (IBT) and urge to impulsive buying on halal fashion products.

A quantitative study was done on 357 Indonesian online shoppers to find out how perceived usefulness and ease of use of mobile shopping apps affect impulsive buying tendencies and urges on halal fashion products. Flow experience and attitude were used as mediating variables, and the research hypotheses were tested using Partial Least Square Structural Equation Modeling (PLS-SEM).

This study confirmed significant positive relationships between perceived usefulness and ease of use of mobile apps, flow experience, attitude, IBT and urge to impulsive buying. The results of this study show that perceived usefulness and ease of use influence flow experience. Ease of use also influences attitude, but perceived usefulness did not impact attitude. In addition, flow experience did not impact attitude. However, both flow experience and attitude influence IBT. Furthermore, IBT significantly mediated flow experience and attitude into urge to impulsive buying.

This study only captured consumers in one country, so its results cannot be generalized to other nations. Random sampling may limit result generalization. In this study, three mobile shopping applications were investigated and the results would have been different if more mobile shopping applications were investigated.

The study gives a better understanding of how the perceived usefulness and ease of use of mobile shopping apps affect a consumer's tendency and urge to impulsive buying on halal fashion products by using flow experience as mediating variable.