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This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects.

The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs.

The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects.

The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV.

The developed approach could be valuable to applications in indoors.

This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

The purpose of this research article is to investigate the critical risk factors associated with the digitalization impact on the Indian construction industry, as these firm plans to implement digitalization in order to improve their construction management processes.

In this research article, risk factors and dimensions are taken from diverse industries and validated in the construction domain by industry and academic experts. Further, multi-criteria decision-making techniques are employed to assess the Indian construction sector scenario quantitatively. The interrelationship and weightage of risk factors and dimensions are determined by the Fuzzy Decision-making Trial and Evaluation Laboratory Analytic Network Process (DANP) method. However, the method Grey Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS) is used to determine the ranking of each risk factor.

This study finds 14 critical risk factors along with four risk dimensions. Operational and financial dimensions are significant risk dimensions. Whereas the threat of high outlay and low yield is a significant risk factor in construction. Besides that, the interrelationship among risk factors, the weightage of each factor and the ranking of critical risk factors are also identified.

This research article uses Fuzzy DANP and Grey TOPSIS techniques as exploratory research methods with a limited group of construction professionals from a leading Indian construction firm. Furthermore, comprehensive confirmatory research can also be performed with a large group of construction experts using advanced analytical techniques to validate the ranking of critical risk factors.

The findings of this study provide insight into the knowledge of construction firms by emphasizing significant risk factors related to digitalization in construction operations. Another finding of this study shows that the risks associated with digitalization in construction are similar to those in manufacturing, where high outlay and low yield hold a significant role in the transformation process.

The research is unique since there have only been limited studies in the Indian construction scenario to analyze the significant risks associated with digitalization. Furthermore, this study demonstrates that the combination of Fuzzy DANP and Grey TOPSIS techniques may be used successfully to prioritize risks in construction digitalization, which is still in its early phases.

The purpose of this paper is to analyze the factors affecting the implementation of unmanned aerial vehicles (UAVs) in Indian humanitarian logistics. The factors listed are significant as they are hindering the incorporation of this new technology into the humanitarian supply chain, thus creating inefficiencies in the humanitarian logistics sector.

This research is approached using a two-step process. In the first step, the particular barriers for UAV implementation are determined by a literature review and consultation with experts. Next, the proposed framework, a combination of grey-decision-making trial and evaluation laboratory (grey-DEMATEL) and analytic network process (ANP), i.e. g-DANP, is used to determine a hierarchical structure for the factors and sub-factors. The grey hypothesis provides sufficient analytical data to an otherwise lacking DEMATEL technique. Also, the use of ANP gives weightage to each factor, allowing us to categorize their importance further.

This study reveals that factors like expensive commercial solutions and high transport energy costs are significant factors of the “cause” group, whereas the uncertain cost for maintenance and repair and deficiency of high-level computing are crucial factors of the “effect” category. The mentioned factors, along with many others, are the main reasons for the delayed incorporation of UAVs in humanitarian logistics.

The results of this study present insights for humanitarian supply chain managers, UAV producers and policymakers. Those in the humanitarian logistics sector can use the findings of this study to plan for various challenges faced as they try and implement UAVs in their supply chain.

This research is unique as it analyses the general factors hindering the implementation of UAVs in Indian humanitarian logistics. The study enriches existing literature by providing an analytic approach to determine the weightage of various interrelations between the identified factors affecting UAV incorporation in the humanitarian supply chain.

The purpose of this study is to carry out the systematic literature review, bibliometric analysis and content analysis of extant literature of service supply chain (SSC).

Systematic literature review (SLR) technique was used for identifying the research papers. In the first step after reading titles, abstracts and keywords and, full-length articles wherever required, papers not related to SSC were removed. In second steps papers were read more critically and papers not related to SSC were removed. Finally on 502 papers bibliometric and content analysis was further carried out. Content analysis was based on the clusters formed by bibliographic coupling. Further, content analysis of the recent articles revealed the current research trends and research gaps.

This paper identified the six existing research diversifications in SSC as (1) logistics SSC, (2) model, framework and conceptual papers, (3) third-party logistics service providers, (4) articles from various perspective, (5) measurement of quality and performance on services and (6) impact of adoption of technology, cooperation and branding on logistics service providers. Further, six future research directions are also provided.

This research provides a clear view of the progression of publication, research diversification, research themes of six identified clusters, sub-themes of clusters and content analysis of each cluster. Content analysis of recent articles reveals the current research trend and future research directions.

This is a first of its kind of study which presents the diversification of research areas within SSC, bibliometric analysis, content analysis and provides actionable future research direction.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Drawing on the resource-based view, ecological modernization theory and upper-echelon theory, this study aims to explore how green manufacturing practices (GMGP) affect the sustainable performance of small and medium enterprises (SMEs).

It also examines the mediating role of green innovation (GIN) and the moderating role of managerial discretion (MD). To test the hypothesized model, the data was collected from 394 manufacturing SMEs though survey and analyzed using SPSS and AMOS (SEM).

The results provide evidence for the positive relationship between GMGP and corporate sustainable performance (CSPR), mediated by GIN. Furthermore, the presence of MD enhances the positive effect of GMGP on CSPR through GIN. Thus, this study enhances the understanding of the relationship between GMGP and CSPR, including its underlying mechanism and conditional effects.

This study collected sample from SMEs located in Punjab province of Pakistan which represents majority of the SMEs; however, future research can take data from other province and with large sample size.

The findings highlight the significance of GMGP and GIN in the manufacturing sector for attaining CSPR goals. GMGP guides business leaders to be more inclined toward the energy and resource consumption as well as waste generation within their organizations which lead to improved CSPR outcomes.

The findings of this study make significant contributions to the existing literature, shedding light on the dynamics between GMGP and CSPR. Moreover, the study offers managerial implications for organizations aiming to enhance their sustainable performance by implementing effective GMGP.

Due to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.

This paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.

The outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.

Selecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.

This study analysed international publications related to the performance evaluation (PE) theme to compare the public and private sectors with a focus on the metrics and a reflection on the consideration of each sector's characteristics.

In total, two bibliographic portfolios (BPs) were selected with the aid of the Knowledge Development Process-Constructivist (ProKnow-C) instrument, and the literature was systematically and critically reviewed to construct a theme literature map; the metrics analysed the performance evaluation systems (PESs) used in the studies and identified each sector's characteristics and PES behaviour based on these characteristics.

The two sectors stand out because of the low incidence of articles with cardinal scales, which enable the measurement and identification of the consequences of performance that are below or above the target. The behaviour of the sector characteristics was unusual, especially regarding the user and the organisational structure; it was found that the presence or absence of critical factors, such as communication, may prove to be a differential of success or failure. An absence of the organisation's particularities when designing and using a PES was noted.

The contributions relate to (1) identification of the public and private sector characteristics based on the selected literature, which helps in understanding the critical success and failure factors of an organisation's PES, especially with regard to metrics adequacy for each context; and (2) verification of the paths taken by the literature in both sectors.