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The overall contribution of this work is to provide a usable maturity model for collaborative scheduling (CS) that extends the literature, identifies inconsistencies in schedule development, and improves collaboration in the construction industry.

Via subject matter expert elicitation and focus groups, the maturity model establishes five pillars of collaboration—scheduling significance, planners and schedulers, scheduling representation, goal alignment with owner, and communication. The maturity model is then validated through iterative feedback and chi-squared statistical analysis of data obtained from a survey. The five pillars are tied to the literature and previous work in CS.

The analysis shows that current industry projects are not consistent in collaboration practice implementation, and the maturity model identifies areas for collaboration improvement. The study's contributions to the body of knowledge are (1) developing a maturity model-based approach to define and measure the current level of collaboration and (2) discovering the level of consistency in scheduling collaboration practice implementation.

The findings provide a benchmark for self-evaluation and peer-to-peer comparison for project managers. The model is also useful for project managers to develop effective strategies for improvement on targeted dimensions and metrics.

The construction engineering and management (CEM) literature does not contain targeted models for scheduling collaboration in the context of maturity and, broadly speaking, neither does the literature at large. The literature also lacks actionable items as presented for the maturity model for collaborative scheduling (MMCS).

This paper introduces the weighting, analysis and validation method used in the development of the Maturity Model for Collaborative Scheduling (MMCS). The scoring and ranking process introduced by the MMCS fills a gap in the literature by supporting the selection of collaborative scheduling (CS) practices that yield more weight toward the achievement of higher maturity levels in the development and implementation of CS. The ranking process can then be used during pre/post project execution to track collaborative scheduling in practice against the model’s weighting and provide the project team with constructive feedback and actionable steps for reaching the next highest level of collaboration.

The MMCS, which focuses on five pillars (key areas of interest for CS) and related swim lanes (specific attributes), covers a broad range of areas in the construction industry and was coded into a survey. The relative weights of pillars and swim lanes were then established using the Delphi method with the group of subject matter experts (SMEs), analyzed using multi-objective decision analysis (MODA) and validated using 241 answers to a survey with questions drawn from the MMCS, including organizations across the industry in the United States.

The project scoring defines bounds for bronze, silver and gold levels of collaboration in scheduling. Project evaluations can then be used to identify areas for continuous improvement and enhanced collaboration. We offer recommendations and best practices for project improvement.

Two original contributions resulted from this work: (1) a method to elicit weights based on a combination of Delphi, MODA and survey methods was used to develop and validate a scale with three different maturity levels to support the use and continuous improvement of CS practices and (2) a validated model was used to assess the maturity level of CS in construction projects alongside specific recommendations to move upward in terms of maturity. In practice, project leaders can use this model to assess project performance, advance the project’s maturity and guide continuous improvement efforts for enhanced collaboration.

The role of nostalgia in consumers’ lives and its application in the design of marketing strategies has been highlighted in prior research. However, the role of nostalgia as well as the consumers’ nostalgic inclination in the development of new products has not been investigated yet, either for existing products or new ones. Hence, the purpose of this paper is to underline and understand the collaborative process of value co-creation for both actors (companies and consumers) in the development of nostalgic new products.

A double methodology was used through a netnographic study (which is inspired by ethnography) and semi-directed interviews. Concerning the netnographic approach, the data collection were conducted on both general and specialized social networks, web sites and forums. The semi-directed interviews were conducted among 12 individuals. The verbatim were analyzed through a content thematic analysis. The use of both methodologies helped to underline recurrent and complementary findings.

The analysis highlights four main results: first, the main criteria for selection and purchase of products and services; second, the perception and dimensions of nostalgia; third, the link between nostalgia and consumption; and finally, the relationship between nostalgic experiences and the co-creation process.

This research is the first to study the value of the co-creation process for the development of nostalgic new products.

The purpose of this research is to examine the potential impact of technologies on enhancing the efficiency and effectiveness of supply chain performance inside healthcare organizations, with a particular focus on cost and quality improvement.

The present investigation employs the survey method to examine the research hypothesis and objective. A total of 630 surveys were collected using an online platform, all of which were deemed to be valid. The gathered data were analyzed using SPSS version 20.0 and Smart-PLS version 3.0 software.

The finding represents a holistic investigation into Industry 4.0 technologies, quality management practices, supply chain performance and organizational performance is essential for the healthcare industry’s evolution. Embracing these elements collectively has the potential to redefine healthcare delivery, improve patient outcomes and drive operational excellence. The results seek to shed light on the broader implications for enhancing patient care, optimizing resources and improving organizational effectiveness within the evolving landscape of Industry 4.0-driven healthcare environments.

Exploration of the incorporation of Industry 4.0 technologies within the healthcare domain has the potential to augment operational efficacy, patient care and data administration. Examination of the repercussions of these technologies on quality management procedures in healthcare environments imparts an understanding of the enhancement of healthcare service quality and patient outcomes.

Implementing Industry 4.0 technologies, which encompass Internet of Things devices and analytics driven by artificial intelligence, within the healthcare sector has the potential to streamline operational procedures, minimize errors and optimize resource distribution. This, in turn, may result in heightened precision of diagnostic procedures, refined treatment strategies and an overall enhancement in the quality of care provided to patients.

There exist certain constraints inherent to this study. In the initial instance, the data were gathered from moderately sizable medical institutions situated within India. As the present investigation was conducted in India, it is possible to examine other countries in order to identify potential disparities in social conditions. Future research should consider, cross-cultural and longitudinal studies of organizational performance.

In the present investigation, the writer presents innovative research that may assist the healthcare industry in identifying the most crucial component of Industry 4.0 technologies for the relevant personnel. There is a notable relationship between the technologies of Industry 4.0 and the supply chain of healthcare, which was formerly the central focus. With a specific emphasis on big data, the Internet of things, cloud computing, blockchain, artificial intelligence and 3D printing, the authors of the current study have showcased a connection between the practice of quality management and the performance of the supply chain by employing industry 4.0 technologies. This paves the way for the healthcare sector to place a heightened emphasis on organizational performance.

In modern times, innovation is considered as a vital component of sustainable competitive advantage. The purpose of this paper is to identify how innovation at the individual level [innovative work behavior (IWB)] and at the organizational level [innovative organizational climate (IOC)] affects the chances of success of a particular project. Additionally, the moderating effect of gender and work culture on the relation between innovative climate and behavior is tested in the study.

Survey technique was used to collect data from 425 employees working in project departments at the executive, middle level and senior level management in the paint manufacturing industry of Pakistan. Multiple regression, as well as Preacher and Hayes (2004) tests, were applied to test the hypotheses.

The result of the data analysis showed that IWB acts as a mediator between IOC and project success (PS), thereby supporting the hypothesized model of innovation and PS. Work culture was supported as a moderator; however, no moderating effect of gender was validated by the results.

The management must make sure that to maximize the rate of success of projects, innovative work climate within the organizations and departments be given due importance. In addition to this, personnel’s individual innovation capabilities must also be enhanced by taking steps toward improvement through training and development.

Though attention has been given to research in innovation in light of other related variables, its relation to PS remains yet to be studied. The effect of gender and work culture on innovation in Pakistani paint industry was long over-due which has been addressed by this study.

Temperature is a critical factor in the fused filament fabrication (FFF) process, which affects the flow behavior and adhesion of the melted filament and the mechanical properties of the final object. Therefore, modeling and predicting temperature in FFF is crucial for achieving high-quality prints, repeatability, process control and failure prediction. This study aims to investigate the melt deposition and temperature profile in FFF both numerically and experimentally using different Acrylonitrile Butadiene Styrene single-strand specimens. The process parameters, including layer thickness, nozzle temperature and build platform temperature, were varied.

COMSOL Multiphysics software was used to perform numerical simulations of fluid flow and heat transfer for the printed strands. The polymer melt/air interface was tracked using the coupling of continuity equation, equation of motion and the level set equation, and the heat transfer equation was used to simulate the temperature distribution in the deposited strand.

The numerical results show that increasing the nozzle temperature or layer thickness leads to an increase in temperature at points close to the nozzle, but the bed temperature is the main determinant of the overall layer temperature in low-thickness strands. The experimental temperature profile of the deposited strand was measured using an infrared (IR) thermal imager to validate the numerical results. The comparison between simulation and observed temperature at different points showed that the numerical model accurately predicts heat transfer in the three-dimensional (3D) printing of a single-strand under different conditions. Finally, a parametric analysis was performed to investigate the effect of selected parameters on the thermal history of the printed strand.

The numerical results show that increasing the nozzle temperature or layer thickness leads to an increase in temperature at points close to the nozzle, but the bed temperature is the main determinant of the overall layer temperature in low-thickness strands. The experimental temperature profile of the deposited strand was measured using an IR thermal imager to validate the numerical results. The comparison between simulation and observed temperature at different points showed that the numerical model accurately predicts heat transfer in the 3D printing of a single-strand under different conditions. Finally, a parametric analysis was performed to investigate the effect of selected parameters on the thermal history of the printed strand.

The aim of this study is to provide a holistic analysis of all possible maritime business logistics processes related to import and export shipments in a fuzzy environment through a case study of a maritime logistics company based on the as-is and to-be models within business process management (BPM).

The analyses considered the following perspectives: (i) in the stage of the process identification, the definition of the problem was carried out; (ii) in the stage of the process discovery, ocean department was divided into ocean export/import operation departments; ocean export/import operation were divided into freight collect/prepaid operation processes; ocean export/import logistics activity groups were broken down into sub-activities for freight collect/prepaid operation; the logistics activity groups and their sub-activities were defined; each sub-activity as either operation or documentation process group was classified; the durations of sub-activities were evaluated by decision-makers (DMs) as fuzzy sets (FSs); the monthly total jobs activities were estimated by DMs as FSs; the applied to monthly jobs activities of total shipments were estimated by DMs as FSs; the durations of each sub-activities were aggregated; the duration of the logistics activity groups and the sub-activities for per job were calculated; the cumulative workload of logistics activity groups and sub-activities were calculated; the duration of sub-activities for per job as operation or documentation departments were calculated, (iii) in the stage of the process analysis, cumulative ocean export/import workload as operation or documentation for freight collect/prepaid were calculated; duration of activity groups and sub-activities for per job as operation or documentation were calculated; cumulative workload activity groups and sub-activities as operation or documentation were calculated, (iv) in the stage of the process redesign, cumulative workload, process cycle time as operation and documentation group and required labor force were calculated; the process cycle time of the theoretical, the as-is model and the to-be model were calculated: (i) the theoretical minimum process cycle time without resource were calculated by the critical path method (CPM), (ii) the process cycle time of the as-is model perspective with the 1 person resource constraint and (iii) the process cycle time of the to-be model perspective with the 2-person resource constraint were calculated by the resource constrained project scheduling problem (RCPSP) method.

The methodology for analyzing the ocean department operation process was successfully implemented in a real-life case study. It is observed that the results of the to-be model can be applicable for the company. The BPM-proposed methodology is applicable for the maritime logistics industry in the present study; however, it can be applied to other companies in maritime logistics as well as other industries.

This study contributes to research using BPM methodology in maritime logistics. This is the first study the logistics process analyses were carried out in terms of including all operation processes for a company. All processes were analyzed by using BPM methodology in maritime logistics. This study demonstrated the application of the BPM as-is and to-be models to maritime logistics. The as-is and the to-be models of the BPM methodology were applied in maritime logistics.

This methodology applied in this study can enable organizations operating in the time-urgent maritime logistics sector to manage their logistics processes more efficiently, increase customer satisfaction, reduce the risks of customer loss due to poor operational performance and increase profits in the long term. Through the use of these methodologies utilizing FSs, the CPM and the RCPSP methods, this study is expected to make contributions to the BPM literature and provide original insights into the field. Furthermore, this study will undertake a comprehensive analysis of maritime logistics with respect to BPM to deliver noteworthy contributions to the maritime logistics literature and provide original perspectives into the field.

This study examines the influence of succession planning and the incumbents’ willingness to step aside on the sustainability of family businesses, a critical but often overlooked aspect that can determine the long-term viability of these enterprises. The study further explores the moderating effect of the incumbents’ willingness to step aside in the relationship between succession planning and sustainability.

The study employs a cross-sectional survey design. Data were collected through structured questionnaires from 190 successors of family businesses in Tanzania. Confirmatory factor analysis was used to validate the measurement model, and hypotheses were tested using the PROCESS macro.

The findings indicate that both succession planning and the incumbents’ willingness to step aside significantly enhance the sustainability of family businesses by ensuring a smooth and structured leadership transition, which minimizes disruptions and safeguards business continuity. Additionally, the incumbents’ willingness to step aside was found to be a significant moderator of the relationship between succession planning and sustainability, meaning that the influence of succession planning on sustainability is much stronger when the incumbents are fully supportive and cooperative during the transition. This implies that without the incumbents’ active participation, even well-designed succession plans may not achieve their full potential.

This study contributes to the limited empirical evidence on the influence of succession planning on the sustainability of family businesses. Additionally, it advances current understanding by identifying the moderating effect of the incumbents’ willingness to step aside on the relationship between succession planning and sustainability, an area not previously explored in the literature. The findings have significant implications for both practitioners and researchers, offering new perspectives on managing generational transitions in family businesses.

This study aims to investigate the effects of three dimensions of ChatGPT strategic value – organization support (OS), managerial productivity (IM) and decision aids (DA) – on the business sustainability (BS) of Malaysian public universities.

A quantitative methodology was adopted for this study to examine the relationships between ChatGPT strategic value and the BS of Malaysian public universities.

The study found that two dimensions of ChatGPT strategic value, namely, OS and IM, influence BS, whereas DA do not.

To the best of the author’s knowledge, this study is the first to address the relationship between ChatGPT strategic value and BS in a specific context – Malaysian public universities – providing new contributions to theory by extending the literature on the topic.

The findings are expected to guide universities in Malaysia in leveraging ChatGPT strategic value for enhancing BS.

To the best of the author’s knowledge, this empirical study is the first in the literature to examine the relationships between ChatGPT strategic value and BS in the education sector. Supported by an original conceptual model, the insights provided should extend the literature dedicated to ChatGPT strategic value and BS in the context of a South Asian economy.