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This study aims to undertake a comprehensive analysis of innovation models, tracing their evolution from Innovation 1.0 to Innovation 4.0 and introducing the concept of Innovation 5.0. It explores the intersection between innovation models and the principles of sustainability, resilience and human-centeredness, providing insights into their implications for Industry 5.0, and their potential to foster a resilient ecosystem amidst challenges and multiple crisis.

To achieve this objective, the authors used a systematic literature review approach, considering academic articles on Innovation 4.0, Industry 5.0 (specifically in the context of innovation) and helix models of innovation. The authors conducted thematic analysis and content analysis, followed by keyword co-occurrence analysis, enabling us to systematically synthesize and interpret the relevant literature.

The results conclude that Innovation 5.0 is a new paradigm for innovation that fosters broader societal engagement, and emphasizes sustainability, resilience and human-centeredness. Innovation 5.0 is evolving, but it has the potential to transform the way we produce, consume and live. Using insights from the sextuple helix model, this research leverages media and ICT as sixth helix vital role of knowledge sharing, digital transformation, innovation ecosystem and next industrial revolution in this process.

This study contributes to the ongoing discourse on exploring Innovation 5.0 through the sextuple helix model, offering a fresh perspective on innovation models and their collaborative potential. Its contribution lies in providing practical insights into the transition to Innovation 5.0, emphasizing the need for sustainability, regulatory support and awareness while also offering clear recommendations for future research.

The purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane.

To achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer.

The finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique.

This paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced.

Although extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

The purpose of this paper is to propose and validate the process of parent teacher meeting in private schools through applying BPM life-cycle approach and using quality tools to fill the gap of standardized practices for parent teacher meeting (PTM).

BPM life-cycle approach (Dumas et al., 2013) was used and two focus groups were conducted at first and second stage. The recommendations of previous studies for third, fourth and fifth stage of BPM and quality tools like SIPOC chart, responsibility assignment matrix (RAM) and CTQ trees were used for process management.

The previous studies reveal that, in developing countries, most of the private schools are not fully aware from the benefits of PTM. Beside, where the evidence of PTM is seen in few instances, no standardized process is available to conduct an effective PTM process. Owing to long-term sustainability and reciprocate economic benefits, school management is desired to have a standardized PTM process for an effective all-round performance. Likewise, the parents have a lot of expectations from schools and they want to be treated in a mannered way in which their complaints are formally addressed from the school management. The authors formulated all three phases from start to end process. The proposed process is validated in four private schools and got satisfactory results in terms of increased parents’ participation and decreased number of complaints.

This process will facilitate school managers to deal with parents effectively, collect the data from PTM, analyze it and use for the continuous improvement. Implementation of this process will ensure better meeting environment for the parents as well as for the teachers. The study bridges between quality management tools and BPM approach to improve the state of art of BPM practices that will lead to generate a trend of application of quality tools and management theories in private schooling industry.

The authors first time used BPM life-cycle approach to manage the process of PTM in private schools. The authors design a process to match the working of schools and the application of desired quality tools.

Despite growing interest in workplace spirituality (WPS) and its impact on employee behaviors, there is a dearth of literature discussing an underlying mechanism of how it affects adaptive performance. Against this backdrop, this study aims to develop and test a comprehensive model that examined the effects of WPS on adaptive performance through serial mediation of job satisfaction and emotional labor strategies.

Using a multi-stage sampling technique, the data is collected from 390 faculty members of the higher education institutions in two-time lags.

The findings indicate that spirituality practices at the workplace help to increase the adaptive performance of employees through serial mediation of job satisfaction and emotional labor strategies.

This study offers important implications to researchers as well as practitioners and highlights the significance of WPS in increasing the adaptive performance of employees.

This research is among the initial attempts to assess the impact of WPS on adaptive performance through serial mediation.

In recent years, China’s growing global economic influence has attracted more foreign workers, requiring leaders to have effective communication skills to manage diverse personnel to drive innovations. Although previous research studies revealed the effects of a leader’s motivating language (ML) on employee’s innovativeness, the mechanism and the boundary conditions for stimulating the relationship between ML and innovative work behavior (IWB) are scarce. Therefore, this study aims to examine employee’s creative self-efficacy (CSE) as a mechanism and coworker support (CS) as a boundary condition in the relationship between ML’s dimensions and IWB.

To test the moderated mediation model, this study collected the data from 283 workers and their respective supervisors at a Beijing-based multinational network company. The research applied a quantitative approach. SPSS and AMOS were used to analyze the data.

ML’s dimensions are positively linked to IWB. CSE was found as a mediator in these relationships. CS did not play its moderation roles on ML – CSE, ML – IWB direct or ML – IWB indirect (via CSE) links. ML’s direction-giving speech is found to be more effective in predicting CSE and IWB.

This is the first paper to examine the impacts of the three dimensions of ML on IWB.

The authors examined how employee led exchange benefits the organizations. Specifically, the authors aim at investigating the mediating role of family supportive supervision between employee performance and taking charge behavior. The authors further examined leader-member exchange (LMX) as a boundary condition between employee performance and family supportive supervision.

The authors collected data from 295 employees and their supervisors working in various public sector organizations of Pakistan on a convenience basis. Specifically, data on family supportive supervision and LMX was collected from employees; whereas, data on employee performance and taking charge was collected from their supervisors between June–September 2021.

The statistical analysis reveals that high-performing employees are reciprocated by the high family-supportive supervision which increases their work-life balance and they further reciprocate by showing a propensity to take charge. In addition, LMX is noted to strengthen the association between employees' performance and family supportive supervision.

This study explains how managers can extend the stream of employees' performance by highlighting the role of family-supportive supervision and LMX. The managers through high LMX and provision of family-supportive supervision can boost the employees' outcomes from job performance to extra-role performance (i.e. taking charge).

This study adds value to the existing body of knowledge by considering performance as a predictor of various organizational-level consequences. Recent studies have considered the negative consequences of employees' performance, while the positive aspect has been called for an investigation.

The purpose of this paper is to explore halal meat production potential and export potential in Pakistan. Following this, the paper is to both stimulate the business and encourage research within this field.

For this study, both primary and secondary data were used. Time-series meat production and export data from 1994-1995 to 2015-2016 were collected from different secondary sources; where primary data were collected from distinguish livestock experts on the possibility of halal meat production in various provinces of the country.

Results show that during 1994-1995 to 2015-2016, annual average growth rates of meat production and export were 3 and 32%, respectively. Based on these growth rates, it was estimated that Pakistan's total meat production and export is projected to be 6,078 thousand tons and $17,477m by 2029-2030. Results regarding the expert opinion survey indicates that Balochistan province has comparative advantage to rare livestock for beef and mutton meat production over rest of the provinces; there is potency for producing chicken meat in Khyber Pakhtunkhwa (KPK) and Punjab provinces, while Sindh province has almost the same efficiency to produce beef and chicken meat.

Experts were in opinion that high yielding livestock breeds should be introduced to farmers; and comprehensive training programs should be designed for all the stockholders involved in meat production, and processing to exports chains. Therefore, it is suggested that registered and corporate livestock farming can be only solution to fulfill required standards of raw and processed meat business in international markets.

At current, halal meat export is considered as major activity of livestock sector of Pakistan: where, this is one of the pioneer studies exploring potential of halal meat production in various parts of the country, which can not only contribute in national income but support the balance of payments of the country.

In the current economic scenario characterized by turbulence, innovation is a requisite for company's growth. The innovation activities are implemented through the realization of innovative project. This paper aims to prospect the promising opportunities coming from the application of Machine Learning (ML) algorithms to project risk management for organizational innovation, where a large amount of data supports the decision-making process within the companies and the organizations.

Moving from a structured literature review (SLR), a final sample of 42 papers has been analyzed through a descriptive, content and bibliographic analysis. Moreover, metrics for measuring the impact of the citation index approach and the CPY (Citations per year) have been defined. The descriptive and cluster analysis has been realized with VOSviewer, a tool for constructing and visualizing bibliometric networks and clusters.

Prospective future developments and forthcoming challenges of ML applications for managing risks in projects have been identified in the following research context: software development projects; construction industry projects; climate and environmental issues and Health and Safety projects. Insights about the impact of ML for improving organizational innovation through the project risks management are defined.

The study have some limitations regarding the choice of keywords and as well the database chosen for selecting the final sample. Another limitation regards the number of the analyzed papers.

The analysis demonstrated how much the use of ML techniques for project risk management is still new and has many unexplored areas, given the increasing trend in annual scientific publications. This evidence represents an opportunities for supporting the organizational innovation in companies engaged into complex projects whose risk management become strategic.