Flexible Management Research Articles

{MFPP(R). An R package for matrix-based flexible project planning

Project planning and scheduling are essential parts of project management. While project planning and scheduling tools are already available to support traditional project management approaches, flexible project management approaches, such as agile, extreme, and hybrid project planning, are less well supported by software tools, especially freely available software packages. To our knowledge, no existing R package for project planning and scheduling can support flexible projects. This paper aims to fill this gap by introducing and describing the R package mfpp for matrix-based flexible project planning/scheduling. This package includes a comprehensive set of tools for project managers to schedule both traditional and flexible project plans. The use of the package is illustrated through examples.

Co-Creating an Inclusion, Diversity, Equity, and Accessibility Strategy: Defining approach and outcomes in a health data research network

BackgroundHealth Data Research Network Canada (HDRN) has committed to strengthening data use to improve health equity. Key this priority is has been an increased operationalization of Inclusion, Diversity, Equity, and Accessibility (IDEA) across the organization and within the data research processes HDRN Canada supports. Missing, however, was a unifying strategy for embedding IDEA within all HDRN Canada initiatives. ApproachGuided by results from an internal environmental scan and network feedback, HDRN Canada began developing an IDEA strategy in 2023. With the end goal of embedding IDEA across all internal teams and across all HDRN Canada strategic goals, collaborative participation methods were chosen to involve all levels of the organization. A process was designed that included focus groups, interviews, and roundtables. ResultsCo-creating the IDEA strategy required broad buy-in including detailing expectations of the planning process in advance. A flexible management approach that enabled the team to adhere to the defined process allowed the Project Team to manage unanticipated challenges. 4 key strategies emerged focusing on learning, data quality and research, leadership, and community engagement. Developing the strategy with co-creative methods helped to identify practical approaches for HDRN to prioritize IDEA within its complex data research initiatives. ConclusionHDRN Canada has outlined its commitment to IDEA in the health data ecosystem. The co-created strategy supports efforts towards accomplishing its organizational objectives and priorities. It is also a valuable resource for those in the health data space working to ensure data research contributes to equitable health outcomes.

Child self-regulation profiles relate to emotion parenting in Black and Latinx mother-child dyads

Across cultures, child self-regulation develops within the parent-child relationship and requires flexible management of one's biology and behaviors. Despite documented relations between self-regulation and adaptive psychological adjustment, research has primarily focused on single indicator assessments of self-regulation within mostly White samples. The present study assessed indicators of self-regulation (i.e., task persistence, positive affect, resting respiratory sinus arrhythmia) in 100 Black and Latinx children (Mage = 6.83 years, SD = 1.50 years) and mother emotion parenting behaviors (Mage = 34.48 years, SD = 6.39 years). Using latent profile analysis, four child self-regulatory profiles were identified. Profile differences by mother emotion parenting behaviors were examined. Controlling for income, ANCOVAs indicated that mothers of children in relatively high self-regulatory profiles showed more positive emotion parenting behaviors when compared to mothers of children in comparatively lower regulatory profiles. Results highlight potential targets for fostering child self-regulation within racial and ethnic minority parent-child relationships.

Flexible Building Energy Management With Neural ODEs-Based Model Predictive Control

Flexible Building Energy Management With Neural ODEs-Based Model Predictive Control

Adapting to Change: How Brick-and-Mortar Retailers Responded to Consumer Behavior Shifts During COVID-19

In response to the drastic challenges brought by the COVID-19 pandemic, brick-and-mortar retailers have had to adjust to the new consumer behaviors quickly. This research paper seeks to analyze and comprehend how these retailers responded differently, as described in each case study: J.C. Penney, Neiman Marcus, Best Buy, and Target, representing a spectrum of impacts and strategic adaptations. Hence, the comparison discovers that J.C. Penney and Neiman Marcus filed for bankruptcy because they could not transform themselves and be competitive under the new norms. Contrarily, the situation did not destroy Best Buy and Target's business as it altered the status quo in their favor. Achieving the flexible management of Best Buy and Target, which concentrated on the economic development of e-commerce interconnection of physical and digital operations, was their key achievement in this turbulent era. Only this way they could face the rising challenges. These scenarios demonstrate the role of adaptability and a well-integrated technology in retail. The result of the study denotes that the business would be able to win against its competitor only if it can adjust itself continuously to the drastic change in consumer behavior, including the rapid growth of online purchasing. The study predicts that the future of retail will likely require ongoing adaptability and take further focus on omnichannel strategies more seriously. It represents a shift from an immediate response to an analysis that investigates the long-term consequences for the retail sector.

Large-scale hydropower dispatching system based on cloud platform and its key technologies

In the past decade, the rapid expansion of hydropower capacity in China brings challenges to hydropower dispatching in data management and operation scheduling. In data management, the scale of hydropower operation data increases explosively, presenting typical big data features. In operation scheduling, the optimization of hydropower system operations is a high-dimension, nonconvex, and nonlinear problem. Conventional optimization methods encounter the “dimensionality disaster”, and cannot solve the scheduling problem efficiently. To deal with these challenges, by analyzing the data characteristics and operation scheduling requirements, this paper develops a large-scale hydropower dispatching system based on the cloud platform. The dispatching system consists of four layers: data access layer, cloud platform layer, data sharing layer, and application layer, which has good scalability and flexibility in data management and operation scheduling. In the application layer, key technologies based on the big data and cloud computing resources of the dispatching system are proposed to carry out the optimal operation of hydropower systems, including distributed parallel dynamic programming (DPDP) for long-/medium-term scheduling and data mining-based method (DMM) for short-term scheduling. Finally, the dispatching system is applied to the operation of hydropower systems in southwest China. Results indicate that: 1) The developed dispatching system is capable of processing 18 million data records per day, with a peak processing speed of 10,000 data requests per second, fulfilling the requirements for hydropower dispatching. 2) In long-term generation scheduling, under varying levels of runoff and plant scales, DPDP has demonstrated a remarkable reduction in computing time compared to dynamic programming, obtaining the same optimal solution with over 90 % less computational time. 3) In short-term peak shaving operation, on typical dry and wet days, the computing time of DMM is 7.2 s and 7.5 s, respectively, far less than the time of mixed-integer linear programming, and the maximum residual load obtained by DMM is lower than historical observations, indicating its effectiveness.

Effects of delay and error in the feedback structure of ecological management

Ecosystems face various emergent uncertainties owing to factors such as climate change and accelerating anthropogenic impacts. Uncertainty is a major challenge and a barrier that ecosystem management faces, because it is difficult to precisely predict a priori risks that can have significant impacts on ecosystems. Hence, management with adaptive capacity is recommended to deal with such uncertainties, and feedback structures are central mechanisms for such flexible management. This study used mathematical models to clarify the specific impacts of feedback structures on ecosystem management, such as resource and wildlife management. In particular, the impact of errors in estimating ecosystem status when providing feedback and the impact of the time lag before feedback effects were implemented into management were examined. Overestimation of ecosystem status or a large time lag led to undesirable temporal oscillations in ecosystem status. However, these scenarios can be avoided when combined with management practices that limit the impact of management on the ecosystem, such as input control. Ecosystem management tends to have a large spatiotemporal scale, and implementing highly accurate monitoring and sophisticated feedback structures is difficult. However, the results suggest that effective ecosystem management with a simple feedback structure can be achieved through such complementary institutional design.

Ultrahigh Stretchable, Highly Transparent, Self-Adhesive, and Environment-Tolerant Chitin Nanocrystals Engineered Eutectogels toward Multisignal Sensors.

Addressing the conflict between achieving elevated mechanical stretchability and environmental adaptability is significant to a breakthrough in the practical application of flexible wearable materials. Therefore, inspired by the perceptive and protective properties of human skin, flexible wearable electronic skins (E-skins) based on deep eutectic solvent (DES) liquid and multiresponse eutectogel have been widely considered to be a promising platform for building a flexible wearable management system to achieve the purpose of "one stone, two birds". In this work, a multifunctional E-skin was designed based on an ultrastretchable, transparent, self-adhesive, and environmentally tolerant eutectogel by first incorporating cationized modified chitin nanocrystals into a covalently cross-linked polymer network comprised of the skeleton formed by a PAA polymerization network structure serving as a stretchable matrix and filled with DESs (ChCl:EG). The obtained eutectogel exhibits superhigh stretchability (up to 6707%), high toughness (17.7 MJ/m3), mechanical strength (0.48 MPa), self-adhesive, and high transparency (91.2%). Simultaneously, the multisignal sensor based on the above comprehensive properties and thermosensitive capacity exhibits a wide monitoring range, high strain/compression/temperature sensitivity, and good reproducibility. Remarkably, the sensor could be attached to rat hearts without glue or stickers for long-term monitoring of high-quality in vivo heartbeat signals. In this way, it is believed that the designed E-skin system based on eutectogel has great potential to serve as a promising platform for the next generation of flexible multisignal monitoring integrated wearable management systems.

Substitutive effects of accounting transparency and corporate governance on firm value

Recently, there has been increasing emphasis on the importance of accounting transparency and corporate governance. While previous studies have individually examined their impact on firm values, this paper investigates their combined effects. Using data from the Compustat and Center for Research in Security Prices databases obtained through Wharton Research Data Services, we measure accounting transparency and company value, and we employ the E-index as a measure of corporate governance. This study conducts firm, year, and industry fixed effects regressions on a large panel dataset comprising 21,476 firm-year observations. According to our research, both accounting transparency and good corporate governance have negative effects on the value of a company. This means that spending money to improve both may end up costing more than it benefits, which could lower the value of the company. These results support the notion that investors may see that maintaining high levels of accounting transparency and corporate governance can be excessively costly, while an overemphasis on these two metrics could potentially limit the flexibility and creativity of management. These findings have implications for managers tasked with achieving a balance between robust corporate governance, enhanced accounting transparency, and corporate value considerations.

Paving the Road While Walking – Perspectives from Flexible Assertive Community Treatment Managers on Preparing the Implementation of Peer Support Work (PSW) in Outpatient Services

This qualitative study explored the perspectives of Flexible Assertive Community Treatment managers on preparation and employment of peer support workers. The study was based on semi-structured interviews with managers (n = 5) in Outpatient Services in the North Denmark Region. The analysis was based on an inductive approach to content analysis which led to three themes: (1) An exploratory but energy-loaded process—deciding to employ peer support workers, (2) Paving the road while walking—preparing employment of peer support workers, and (3) Uncertainty about the “how” and the “what”—preparing mental health professionals for collaborating with peer support workers. Together these themes describe an exploratory and unstructured implementation process, revealing a lack of structure during implementation. Such circumstances are known to potentially compromise staff wellbeing, feeling insecure about own professional role, and lack of readiness to embrace peer support workers as colleagues. Applying an implementation framework and addressing the literature on barriers and facilitators may promote successful implementation of peer support worker employment.

Investigating Students’ Perceived Satisfaction and Performance in Online Class: Basis for Online Learning Improvements

The landscape of education has experienced significant changes as a result of the global COVID-19 pandemic. Central to the recent developments is the increasing concerns related to the levels of student satisfaction and performance in Mathematics within the context of online learning. This study seeks to fill the gaps in existing research literature on how mathematics is taught online during the pandemic. In particular, the goal of this research was to investigate the relationship between students' perceived satisfaction and reported academic performance in a Mathematics online class and suggest important satisfaction factors to improve student online learning experiences. The study was a descriptive research design utilizing mixed methods, and the data were collected from a volunteer sample of ???? = 153 respondents, composed of senior high school students from three private schools, through an adapted online survey instrument. Results showed that the association between satisfaction and performance was significant and positively correlated. Furthermore, there was a low but positive significant correlation between satisfaction with their performance. Regardless of their performance levels, students were generally satisfied with online learning. Students, however, pointed out three (3) additional factors that affect their satisfaction – flexible and considerate task management, effective communication and subject mastery in teaching; and accessibility and clarity of educational resources. To improve online learning, these additional factors are essential to have a high level of satisfaction and performance in online learning.

Optimization of cutting parameters in manufacturing of polymeric materials for flexible two-phase thermal management systems

Abstract This research study with an extensive literature review represents a comprehensive multi-criteria analysis for optimizing the cutting parameters in the manufacturing of flexible two-phase passive thermal management systems (FTP-TMS) using thermoplastic materials. Recognizing the critical role of thermoplastics in FTP-TMS due to their inherent flexibility and lightweight properties, this research focuses on the precision cutting of polypropylene, polyethylene, and polyvinyl chloride using CO2 laser technology. The study is structured into three distinct phases. Initially, an experimental setup was conducted to cut 2 mm thick thermoplastic materials with varying power and cutting speed parameters. Subsequently, the SWARA method was employed to weight the criteria, followed by the application of seven different multi-criteria decision-making (MCDM) methods for optimization. The final phase involved a detailed analysis of the outputs, including ranking, correlation, and sensitivity analyses. The findings indicate that cutting polypropylene with a 90 W power setting and a speed of 15 mm s−1 yields the most optimal results. This study fills a significant gap in the existing literature by providing a dedicated analysis for thermoplastics in FTP-TMS manufacturing. The insights gained are pivotal for standardizing manufacturing practices and enhancing the design and fabrication of flexible thermal management solutions, offering substantial benefits to sectors like electronics, aerospace, and automotive industries.

The Impact of Cognitive Distortions on Decision Making in Agile Project Management Frameworks: Current Positions and Perspectives in the Academic Community

The purpose of the study is to review the current positions and views of the scientific community regarding the influence of cognitive distortions (both individual and group) on decision-making within such an approach to project management as agile framework. The article defines the concepts of “project”, “project management”, “agile project management framework”, “heuristics”, “cognitive distortions”; it describes what kind of decisions (according to the hierarchical structure) can be made when using agile project management frameworks. On the basis of analysis of a number of scientific works, the existence of the problem of success (efficiency) of implemented (including IT) projects even if modern flexible frameworks of project management are used is fixed. The author of the study considers the concept of heuristics and cognitive distortions (both individual and group), describes the manifestation of individual and group cognitive biases, gives examples of individual and group cognitive biases’ impact to decisions taken in Agile project management. As a result, the author proposes a classification of likely to manifest individual and group cognitive biases at each of the three levels of decision-making in Agile (according to the hierarchical structure): operational decisions, tactical decisions, strategic decisions. The author also provides an overview of the development of decision-making theory and describes three main approaches to the consideration of the empirical decision-making process: according to D. Kahneman and A. Tversky (heuristic approach; behavioral economics), according to G. Gigerenzer (ecological rationality approach), according to G. Klein (naturalistic approach). The author also identifies a possible further vector for the development of research in this direction. The result of the work was the classification of probable individual and group cognitive distortions at each of the three levels of decision-making in flexible project management frameworks (according to the hierarchical structure): operational, tactical, and strategic.

Flexible supply-demand side management towards a sustainable decentralized distribution network: A net-negative Water-energy-emissions Nexus assessment

Severe water and energy shortfalls hinder widespread access and challenge sustainable resource management in various supply systems. This study proposed a new decentralized distribution network with net-negative emissions concept and flexible strategies to ensure efficient water and mix-energy with low-carbon emissions The proposed net-negative water-energy emission decentralized distribution network (N-NWEE-D2N) was formulated by assessing spatio-temporal interactions at local-regional scale of multi-sector water and energy demand and supply using flexible nexus regulation strategies. The feasibility of self-production and CO2-based regeneration from biogas recovery in activated sludge process and non-renewable energy generation, respectively, was investigated. The N-NWEE-D2N-based water-energy distribution showed an effective balance between supply and demand, with low deficits, efficient surplus utilization, and reduced CO2 emissions. The water and energy management efficiencies based on N-NWEE-D2N improved by 67.196% and 78.11%, respectively, compared to scenarios without such considerations, due to the effective decentralized distribution of water and energy among the regions. Thus, proposed N-NWEE-D2N can contribute to the sustainable operation of WWTPs and promoting long-term sustainability in water and energy distribution transmission.

Economic Factors and Performance of Selected Quoted Consumer Goods Manufacturing Companies: The Moderating Roles of Firm Agility

The problem of this study is the significant decline in the performance of consumer goods manufacturing companies, which is caused by various economic factors such as import policies, inflation, infrastructure, interest rates, and exchange rates. This study aims to evaluate the impact of economic factors on the performance of publicly traded consumer goods manufacturing companies and test how corporate agility moderates this relationship. The study employed a cross-sectional survey design with a population of 5,625 employees from 12 companies, yielding a final sample of 563. Data was collected through a questionnaire validated by confirmatory factor analysis and measured by a Likert scale. Data analysis was conducted with multiple regression using SPSS version 22.0. The results show that economic factors significantly affect firm performance, and firm agility significantly moderates this relationship. The conclusion of this study suggests that consumer goods manufacturing companies need to improve their agility to overcome the negative impact of economic factors. This study implies the need for more adaptive and flexible management strategies to enhance firm performance in the face of dynamic economic challenges.

Digitization of logistics and supply chain management

The article presents theoretical and applied aspects of digitalization of logistics and supply chain management. It is emphasized that the processes of digitalization of supply chains and logistics are a modern requirement for increasing business efficiency, as well as solving environmental, social and management problems of successful companies. Digitization of supply chains and logistics is defined as the integration of digital technologies and the implementation of digital tools to optimize, automate and increase the efficiency of all stages of the logistics process. Key modern technologies in logistics and supply chains are examined, including artificial intelligence (AI), the Internet of Things (IoT) and Big Data. The role of AI in optimizing logistics processes, forecasting market behavior, inventory management and route planning is outlined. Emphasis is placed on the importance of IoT for tracking goods, monitoring storage conditions and vehicle maintenance. The role of Big Data in optimizing supply chains, improving decision-making and compliance with regulatory requirements is analyzed. The use of digital documentation and electronic document circulation are highlighted as important areas of digitization. The difference between digitization of documents and digitalization of document circulation is revealed: digitization, or digital preservation, refers to the transfer of information from paper documents to electronic format for convenient and safe storage of files and access to them in the future; digitalization involves the creation of documentation in computer applications, its intelligent processing and analysis, its accumulation in digital repositories, and the wide use of its data to solve various problems. It is noted that one of the main directions of digitization of documents is the automated reading of documents and data entry, which is implemented using specialized software for automatically extracting information from paper documents and entering it into digital systems. The list of the main logistics documents that are subject to digitization and the digitization of which leads to an increase in the efficiency of the supply chain (delivery confirmation, bill of lading, packing lists, invoices, cargo manifest, etc.) is provided. It was concluded that digitalization of logistics is a significant factor for modern companies seeking to increase their competitiveness in the market. It also enables the integration of all company divisions, improves product tracking, speeds up customs procedures, optimizes transport costs and increases the flexibility of return management. Despite the shortcomings that accompany this process, digitalization of logistics is necessary to achieve sustainable development and effective management of supply chains in today's world.

Reverse logistics capabilities and supply chain performance in a developing country context

ABSTRACT Today and in the highly complex pharmaceutical industry, reverse logistics is a core capability for pharma companies that seek competitive advantages from the efficient management of returns and recalls, e.g. due to errors, expired stocks, quality-related or environmental issues, non-compliance and other consumer-related concerns. And yet in many developing countries where the pharma industry is a big part of the economy, the value of RL is not well understood. In this study, we examine the ambivalent impact of reverse logistics capabilities within the pharmaceutical supply chains in a developing country by focusing on four key reverse logistics capabilities, i.e. logistics information systems, process formalisation, flexibility, and top management support. The findings show that logistics information management systems, process formalisation, and flexibility significantly affect supply chain performance of pharmaceutical firms. However, the hierarchical regression found no significant moderating effect of top management support between reverse logistics capabilities and supply chain performance. Our subsequent discussion and implications for practice and future research are based on these findings.

Characterization of Intrinsically Disordered Proteins in Healthy and Diseased States by Nuclear Magnetic Resonance.

Intrinsically Disordered Proteins (IDPs) are active in different cellular procedures like ordered assembly of chromatin and ribosomes, interaction with membrane, protein, and ligand binding, molecular recognition, binding, and transportation via nuclear pores, microfilaments and microtubules process and disassembly, protein functions, RNA chaperone, and nucleic acid binding, modulation of the central dogma, cell cycle, and other cellular activities, post-translational qualification and substitute splicing, and flexible entropic linker and management of signaling pathways. The intrinsic disorder is a precise structural characteristic that permits IDPs/IDPRs to be involved in both one-to-many and many-to-one signaling. IDPs/IDPRs also exert some dynamical and structural ordering, being much less constrained in their activities than folded proteins. Nuclear magnetic resonance (NMR) spectroscopy is a major technique for the characterization of IDPs, and it can be used for dynamic and structural studies of IDPs. This review was carried out to discuss intrinsically disordered proteins and their different goals, as well as the importance and effectiveness of NMR in characterizing intrinsically disordered proteins in healthy and diseased states.

Strategi Manajemen Budaya Akademik dalam Meningkatkan Absensi Mahasiswa di STITNU Al-Farabi Pangandaran

This research explores academic cultural practices in the campus environment and its impact on increasing student absenteeism at STIT NU Al-farabi Pangandaran. The method used is participatory descriptive qualitative with a phenomological approach. Data was obtained through complete participant observation and in-depth interviews with students and lecturers as well as analysis of related documents. .The results of the research show that many students at SIT NU Al-Farabi Pangandaran work part time, student involvement in campus organizations and personal problems are the main problems that influence the increase in absenteeism on campus, students who work part time often experience conflicts between schedules. work and study schedules. These findings underscore the need for appropriate intervention by improving academic culture so as to increase lecture attendance on campus, with a focus on flexible time management and improving academic discipline.

Decentralized energy management regime for prosumer community Microgrids using flexible tube model predictive control

Achieving reliable, cost-effective, and low-carbon energy management for community microgrids (CMs) under suitable computational complexity is challenging due to uncertainties in renewable generation and load demand. To address this challenge, this paper proposes a flexible tube model predictive control-based energy management regime (EMR) for prosumer CMs, enabling robustness against system uncertainties in the energy management strategy with fewer sacrifices in economic performance and computational efficiency. The proposed EMR adopts a multistage receding horizon optimization structure, which allows the prosumers to dynamically adjust their energy scheduling according to the updated energy price and forecast information. Further, a decentralized algorithm with a conditional communication strategy is developed, highlighting less communication burden and private information preservation. Case studies on a typical prosumer CM demonstrate the effectiveness of the proposed method in confronting high system uncertainties. Notably, the proposed method ensures that CMs operate with high reliability (having a maximum energy supply shortage probability of just 0.42 %), in a low-carbon and economical manner (the local accommodation rate of renewable energy generation with low costs reaches 98.83 %), even in scenarios where disturbances occur simultaneously on both the energy supply and demand sides.