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Notable energy losses and voltage deviation issues in low-voltage radial distribution systems are a major concern for power planners and utility companies because of the integration of electric vehicles (EVs). Electric vehicle charging stations (EVCSs) are the key components in the network where the EVs are equipped to energize their battery. The purpose of this paper is coordinating the EVCS and distributed generation (DG) so as to place them optimally using swarm-based elephant herding optimization techniques by considering energy losses, voltage sensitivity and branch current as key indices. The placement and sizing of the EVCS and DG were found in steps.

The IEEE 33-bus test feeder and 52-bus Indian practical radial networks were used as the test system for the network characteristic analysis. To enhance the system performance, the radial network is divided into zones for the placement of charging stations and dispersed generation units. Balanced coordination is discussed with three defined situations for the EVCS and DG.

The proposed analysis shows that DG collaboration with EVCS with suitable size and location in the network improves the performance in terms of stability and losses.

Stability and loss indices are handled with equal weight factor to find the best solution.

The proposed method is coordinating EVCS and DG in the existing system; the EV integration in the low-voltage side can be incorporated suitably. So, it has societal impact.

In this study, the proposed method shows improved results in terms EVCS and DG integration in the system with minimum losses and voltage sensitivity. The results have been compared with another population-based particle swarm optimization method (PSO). There is an improvement of 18% in terms of total power losses and 9% better result in minimum node voltage as compared to the PSO technique. Also, there is an enhancement of 33% in the defined voltage stability index which shows the proficiency of the proposed analysis.

This paper aims to determine the demand category and level of government and investors in public–private partnership (PPP) projects. It emphasizes the importance of meeting the demands of stakeholders and controlling the unreasonable demands. This study aims to improve the demand management of stakeholders in the PPP project and lay a foundation for the research on behavior based on the motivation theory.

This paper opted for a questionnaire survey to collect data based on indicators identified through literature. The participants come from the government and private sector (investors, contractors, operators, etc.) in China PPP Lecture Hall. The reliability, validity and variance analyses are used to test the reliability of data. Factor analysis and entropy method are used to determine demand categories and weights.

The government’s 14 demands are divided into four groups: satisfy public activities, self-interest, responsibility and relief financial pressure; 6 investor's demands are divided into development ability and satisfy social activities. The self-interest of government is higher than that of the publicity in PPP projects; investor's social reputation is most important, it is a foundation for obtaining external resources and achieving enterprise development.

Because of the chosen research approach, the demand indexes cannot be exhausted. Therefore, researchers are encouraged to enrich relevant contents further.

This paper includes implications for a targeted demand control mechanism and for managing the unreasonable demand.

This paper comprehensively identifies the demand hierarchy of the government and investors, and provides the theoretical basis for the target management of stakeholders.

Delivering housing to resource-constrained communities (RCCs) is a complex process beset with difficulties. The purpose of this study is to use a complexity lens to examine the approach taken by a social enterprise (SE) in Australia to develop and manage a housebuilding supply chain for RCCs.

The research team used a longitudinal case study approach from 2017 to 2022, which used mixed methods to understand the phenomenon and gain an in-depth understanding of the complex issues and problem-solving undertaken by an SE start-up.

Balancing mission logic with commercial viability is challenging for an SE. The supply chain solution that evolved accommodated the particulars of geography and the needs of many stakeholders, including the end-user community and government sponsors. Extensive and time-consuming socialisation and customisation led to a successful technical design and sustainable supply chain operation.

Analysing supply chain intricacies via a complexity framework is valuable for scholars and practitioners, assisting in designing and developing supply chain configurations and understanding their dynamics. Meeting the housing construction needs of RCCs requires the SE to place societal focus at the centre of the supply chain rather than merely being a system output. The developed business model complements the engineering solution to empower a community-led housing construction supply chain.

This longitudinal case study contributes to knowledge by providing rich insights into the roles of SEs and how they develop and operate supply chains to fit with the needs of RCCs. Adding a contextual response dimension to an established complexity framework helped to explain how hybrid organisations balance commercial viability demands with social mission logic by amending traditional supply chain and governance practices. The case provides insights into supply chain configuration, needed changes and potential impacts when an SE as a focal actor inserts into a traditional for-profit construction supply chain.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The purpose of this paper is to explore and describe the perspectives and reasoning of senior development leaders in healthcare organizations, when reflecting on design as theory and practice in relation to more traditional methods and tools for improving quality and support innovation.

The paper is based on a qualitative interview design with five development and innovation leaders from separate healthcare regions in Sweden. They have, to varying degrees, applied design theory and practice for quality improvement and innovation in their organizations. The interview transcript was analysed using a content analysis together with an interpretive approach.

The major findings are to be found in the balancing act for leadership and organizations in healthcare when it comes to introducing and combining different theories and practices for improving quality and support innovation. The balance is between the change in power dynamics and pushing traditional boundaries in a complex healthcare world.

The narratives from the leaders' experience of applying design theory and practice for improving healthcare quality can help us create readiness and knowledge about how we prevent and/or facilitate planning and implementing design theories, practices, methods and tools in a healthcare context.

The study provides a unique insight when it captures and illustrates five different organizations' experiences when applying design for developing healthcare quality.

A paradigm shift of industry revolution 4.0 is made possible by technological advances that constitute a reversal of conventional lean production (LP) processes. In addition, there is increasing pressure on the manufacturing industry to manage operations responsibly towards the environmental and social impact, on top of the economic. These have motivated the manufacturing industry to identify approaches to implementing LP to achieve sustainable organizational performance. Hence, this study aims to examine the moderating role of industry 4.0 technologies adoption in the relationship between LP and sustainable organizational performance.

This study proposed a research framework on the relationship between LP and sustainable organizational performance supported by LP theory and triple bottom line theory, with industry 4.0 technologies adoption as a moderator. A quantitative survey method was used in this study for data collection. The respondents in this study were middle or top management in manufacturing companies, including directors, managers, supervisors and coordinators. To investigate the demographic variables of respondents, descriptive statistics were generated by using IBM Statistical Packages for the Social Sciences. For measurement and structural model evaluations, partial least square structural equation modelling was used.

Based on the proposed research framework in this study, supplier feedback, just-in-time delivery, supplier development, customer involvement, pull system, continuous flow, set-up time reduction (STR), statistical process control, total productive maintenance (TPM) and employee involvement are the dimensions for LP. This study revealed that industry 4.0 technologies adoption positively moderated the relationships of five LP dimensions towards a sustainable organizational performance, namely, supplier feedback, supplier development, continuous flow, STR and TPM.

This study provided insights that would enable practitioners to better strategize the co-existence of LP and industry 4.0 technologies adoption in mutually supporting sustainable organizational performance (environmental, social and economic).

Fintechs are expected to develop rapidly as technologies that help improve the efficiency of the traditional financial system, but an examination of fintech subbranches shows different behaviors. In some sub-branches, the transition has been accompanied by a higher speed and more success, but in some other sub-branches, the opposite has been observed. The difference in the development of fintech sub-branches and its reasons have been paid less attention. Therefore, this article aims to identify the factors affecting the transition.

The use of new technologies in financial services at the international level has led to the provision of fast, customized and economical services, and the fact that these services are welcomed by the users has created opportunities for fintech's transition. This qualitative research follows the socio-technical phenomenon of fintech transition through narrative research. For its formulation, the transition process of fintech sub-branches was analyzed based on the multi-level analytical framework and Geels et al.’s transition path theory.

Transition is a change from one socio-technical regime to another. The findings of the research showed that these changes are influenced by the following factors: provision of infrastructure, the support of industry incumbents from innovative financial services, policy-making, citizen's welcoming, improving the knowledge and expertise of actors, legal adjustments as well as provision of innovative services.

The fintech transition has a special nature because the speed of developments in fintech is high and there is a series of innovations that are continuously replaced by subsequent innovations. Existing models have often focused on the long-term transition of a technology. This article presents a new approach for the analysis of changes in the short term in such a way that, based on the position of the actors in favor of or against the technological changes and institutional changes of the transition, it has analyzed and identified the factors affecting the transition. By focusing on these factors, policymakers can direct the way of fintech transition and help accelerate and facilitate fintech transition.

This study aims to develop a taxonomy of requirements for mobile BIM technologies (MBT), clarify the relating terms and concepts, and identify the interactions between MBT features and the construction management functions on sites.

A positivist approach with elements of interpretivism is adopted to allow to capture what is perceived as “reality” in relation to individuals’ interpretation and experience in the use and implementation of MBT. This is achieved by using a mixed qualitative-quantitative approach that can capture the various understandings of MBT. The research methods included a longitudinal case study over 12 months, two project workshops, expert interviews and an industry survey that together helped to investigate MBT at project, enterprise and industry levels.

The MBT requirements taxonomy included requirements relating to both project and organisation. Project requirements addressed MBT functionalities for sites and information management, while organisation requirements focused on the integration of MBT solutions with the enterprise from information technology, legal and security perspectives. A detailed matrix showing the interactions between five key MBT features and seven construction management functions was also developed.

The two constructs developed by this study can help researchers to structure their investigation of key uses of MBT applications and their benefits. It can be used by researchers aiming to investigate integrated approaches to the digitalisation of construction sites, such as those enabled by Digital Twins. The interaction matrix can aid researchers in evaluating the intersections between the MBT functionalities and the site construction management functions (e.g. theoretical analysis of interactions from Lean Construction, benefit evaluation perspective). More broadly, the two constructs can support research and practice investigating the development of data-driven approaches on construction sites.

The developed MBT taxonomy can guide construction organisations in selecting suitable MBT for Field BIM for their projects. It can also act as a baseline against which varying MBT solutions can be compared.

Constructs such as taxonomies for MBTs; an understanding of MBT capabilities and use within the industry; and a lack of delineation between related terms, such as Mobile BIM, Field BIM, Site BIM, Cloud BIM and Mobile Apps, were lacking in the literature. This study contributed to addressing this gap.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.