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The aim of this paper is to generate a streamlined, transparent and effective instrument to fairly measure the contribution made by each student to a group project within a higher education context. The primary aim is to moderate the grades of underperforming students at the end of the project. There is a secondary benefit in alerting underperforming students to raise their contribution mid-task or face a potentially reduced grade at the final stage.

The development of this multi-dimensional instrument is guided by findings from previous research. The quest is to minimise the instructor's administrative work load in applying a moderation-only instrument that is open-source and available at no cost. Based on the literature, the survey instrument seeks to apply a peer-based, equitable and transparent evaluation of each member's contribution to a group task. The survey is applied at mid-task and again at end-task in order to afford underperformers the opportunity to address contribution deficits during the final phase of the project.

The instrument, called TANDEM©, offers a transparent, streamlined, equitable, confidential and practical measure of each student's contribution to a graded group task. Students whose end-task contribution falls below the group average rating receive a proportional reduction in their personal grade. Additionally, the end-task moderation instrument captures a single-item holistic measure of relative contribution that may, in the future, serve as a surrogate for the multi-dimensional measures currently in place.

TANDEM© was developed with group sizes of four or five members in mind. There is no evidence to support its application to three-person groups. Moreover, the application was applied only amongst under-graduate students. It is yet to be applied across post-graduate groups and within online learning environments. Future research into diverse cultural settings would serve to advance understanding of how moderation is perceived across borders.

Several existing group grade moderation methods propose complex algorithms that are “black box” solutions from a student's perspective. In establishing a fair, streamlined, confidential and transparent process for peer-rated moderation, TANDEM© deploys a concise instrument with a relatively small administrative load. TANDEM © may be applied to all groups or can selectively be applied to groups that report moderate, strong or extreme levels of conflict.

Students will appreciate the opportunity to rate peer contributions to group projects. This will dissipate the negative social sentiment that may arise when fellow students benefit from the work of others. Those students seeking conflict resolution within the group will value the transparent and equitable moderation of grades as well as the positive social implications that follow.

This research forms part of an ongoing quest to present a moderation instrument that fairly identifies student contribution to a group project. Whilst the solution proposed is one of many existing alternatives, its focus is on a practical moderation-only instrument that can immediately be applied to a course or major. The benefits lie in the ease of application and minimal administrative workload. This constitutes an original contribution to the individual (course or major) coordinator who seeks to apply a moderation-only instrument without having to commit to an extensive, broad-based group optimisation programme.

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.

The purpose of this study is to address the significant impact AVs will have on public services and the ability of first responders to conduct their jobs safely and effectively. Autonomous vehicles (AVs) are expected to drastically change the transportation industry, and it is vital that first responders be equipped to integrate them into their occupational responsibilities.

A systematic literature review was conducted, and following a multistep exclusion process, 161 articles were selected for detailed review. The impacts of AVs on first responders were identified, classified and categorized into lists of challenges and opportunities. Based on the findings of the literature review, a SWOT (strengths, weaknesses, opportunities and threats) analysis was conducted, and stakeholder management strategies were designed.

Through the examination of the impacts of AVs on first responders, 17 identified challenges and opportunities were classified into the following categories: AV-related emergency response and training, perceptions and acceptance of AVs, technology development and laws and regulations. The study revealed that the optimal benefits of AVs would require stakeholders to focus more on how they interact with first responders; thus, 14 stakeholder management strategies were identified. First responders, AV manufacturers, legislators and future research paths will all benefit from this study, as it can facilitate smooth interactions between AVs and first responders.

A range of studies have been published on the safety of AVs and the public’s perceptions of this new technology; however, the integration of AVs and their interactions with first responders has been neglected. The goal of this study was to fill that research gap by providing a thorough synthesis of autonomous driving systems in the context of their interactions with first responders.

This study uses big data analysis aimed at discovering city bus passenger ridership patterns. Hence, marketing managers can get sufficient insights to formulate effective business plans and make timely decisions about company operations.

This study uses a mixed-method analysis to analyze the results. First uses the RFM (recency, frequency, and monetary) model combined with a big data technique (K-means) to analyze bus passenger boarding behavior. In order to improve the validity and quality of the research, this study also conducted interviews with senior managers of the bus company from which the data was obtained.

The study identifies six distinct groups of passengers with different boarding behaviors, ranging from “general passengers” to “most valuable passengers”. General passengers constituted the largest group. As such, they should be the main target for municipal governments when promoting bus ridership as part of energy conservation and carbon-reduction activities. This group of passengers should be encouraged to take public transport vehicles more, instead of relying on personal vehicles. The fourth group identified included elderly passengers with hospitals as their destinations. Bus companies can cooperate with municipal government to provide morning “medical bus” services for the elderly. Interviews with bus company managers confirmed that the analytical results of this study correspond with the observations, experiences, and actual business operating plans of bus companies.

Only few studies have analyzed passengers' boarding behavior applying a mixed-method analysis.

Strategic integration of enablers and the realization of drone delivery benefits emerge as essential strategies for business organizations to enhance operational efficiency and stay competitive in last-mile logistics. This paper aims to explore the benefits of drone-based last-mile delivery in the Indian logistic sector by providing a framework for ranking drone delivery benefits (DDBs) due to the adoption of its enablers.

This study proposes a novel hybrid framework applied in the Indian logistic sector by integrating a sentence boundary extraction algorithm for extracting benefits from literature, a spherical fuzzy analytical hierarchy process (SF-AHP) for evaluating primary enablers, unsupervised fuzzy C-means clustering (FCM) for clustering benefits and a spherical combined compromised solution (SF-CoCoSo) for ranking benefits with respect to primary enablers.

The results reveal that technological and infrastructure enablers (TIE), government and legislation enablers (GLE) and operational and service quality enablers (OSE) are the most significant enablers for drone implementation in logistics. Top-ranked benefits increase the efficiency of last-mile delivery (DDB10), foster supply chain management and logistic sustainability (DDB16) and increase delivery access to rural area and vulnerable people (DDB17).

This research assists scholars, entrepreneurs and policymakers in the sustainable deployment of drone delivery in the logistics sector. This study facilitates the use of drones in delivery services and provides a foundation for all stakeholders in logistics.

The assessments involve considering judgment from a highly knowledgeable and experienced group in India, characterized by a large volume of inputs and a high level of expertise.

This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.

Given the growing emphasis on environmental consciousness and sustainability as core principles within most companies, product-service systems are recognized as strategic approaches to achieving sustainability objectives. Consequently, understanding consumer acceptance of these systems is of paramount importance. This study seeks to explore users' perspectives on the barriers that impede the adoption of product-service systems, intending to prioritize these obstacles.

This study utilizes a social media-based approach, specifically analyzing tweets related to Zipcar, an American car rental company that exemplifies a usage-oriented product-service system. The analysis identifies the factors influencing the acceptance of this system. The study utilizes topic modeling and sentiment analysis techniques to analyze the tweets. The opportunity value of each topic is determined, aiding in the identification of topics that require improvement. Furthermore, the interrelation between topics is explored, followed by correlation analysis to assess their significance.

Eight topics strongly related to the keywords are identified. Among them, “responsiveness”, “responsibility”, and “trust” hold the highest opportunity values. The findings emphasize the importance of service providers proactively addressing the obstacles that impede consumers' willingness to adopt product-service systems. Prioritization should be given to topics with higher opportunity values.

This research uncovers the primary obstacles to adopting the product-service system by directly considering consumer opinions and providing a prioritized list of these obstacles.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

Managerial “awareness” of supply chain management (SCM) principles is a key antecedent of SCM adoption. However, supply chain awareness (SCA) provides fertile ground for further development. The authors combine extant research with the attention-based view of the firm to further develop SCA and theorize about its effect in an understudied context.

The authors combine SCA with supply chain orientation, of which awareness is central. The authors combine qualitative and archival data for a 10-year period to test SCA in nonprofits. SCA was measured unobtrusively to avoid respondent bias; then, the authors explore how SCA relates to revenue generation from services provided.

SCA correlates positively with revenue generation. Drawing on a contingency perspective, the authors test two moderators relevant to nonprofits. The positive effect of SCA on revenue is stronger for nonprofits collocated in cities with corporate headquarters but weaker for those with larger boards.

The study further advances the notion of awareness for studying SCM phenomena and provides evidence of its relevance in the unexamined context of human services nonprofit organizations (NPOs). This work has implications for how attention to SCM principles shapes organizational outcomes, the factors that moderate these relationships and the importance of unobtrusively measuring awareness in SCM research. The authors used WayBack Machine to harvest websites. However, the quality and depth of text obtained prior to 2008 were lower than those of later years. Additionally, archival data for NPOs are limited.

Findings inform about the fit between nonprofit resources, type of board and fit with how to fund operations. This research provides an alternative way for policy makers to assess NPO capacity by focusing on the fundamental SCM concepts.

The authors contribute to the dialogue about NPOs developing financial independence through revenue generation from services sold to end customers.

NPOs are seldom studied in SCM. This is an attempt to study NPOs by combining qualitative and quantitative data.

The purpose of this research is to assess how full-time tenured academic staff promotion practices (SPP) in Malaysian private universities (MPUs) influence academic staff engagement (SE) and academic staff performance (SP).

The research used quantitative and descriptive methods, focusing on MPUs' academic staff as the unit of analysis. Sampling involved simple random and stratified techniques, with 314 academic personnel surveyed. Participant data was collected through a questionnaire, and study hypotheses were tested using partial least squares structural equation modeling (PLS-SEM) via a bootstrapping approach.

The findings show that SE somewhat mediates the connection between SPP and SP and that SPP significantly influences SP.

This study emphasizes the importance of impartiality and transparency within university administration when promoting academic staff. Universities should adopt modern strategies and approaches for advancing their employees to higher positions, doing so will motivate employees to fully invest in their work, leading to sustained high-performance levels.

This research has substantially improved the understanding and the practical utilization of literature about SP, SPP and SE. This improvement can potentially facilitate the development of models, theories, research initiatives, and practical strategies geared toward enhancing staff efficiency.