Management Software Research Articles

The Future of Performance Management: Shifting from Annual Reviews to Continuous Feedback

Abstract: The landscape of performance management is undergoing a significant transformation, moving away from the traditional model of annual reviews toward a more dynamic and continuous feedback approach. This shift is driven by the need to adapt to the rapidly changing work environment, where agility, employee engagement, and real-time performance improvement are becoming increasingly critical. This chapter explores the evolution of performance management, examining the limitations of annual reviews and the growing demand for more frequent, constructive feedback mechanisms. Continuous feedback not only fosters a culture of ongoing development but also aligns employee objectives with organizational goals in realtime, enhancing overall productivity and job satisfaction. The discussion highlights the technological advancements, such as performance management software and AI-driven analytics, that are enabling this shift, making it easier for organizations to implement and sustain continuous feedback systems. Additionally, the chapter delves into the challenges and considerations that come with this transition, including the need for managerial training, the potential for feedback overload, and the importance of maintaining a balanced approach that supports both individual growth and team collaboration. Through a combination of theoretical insights and practical case studies, this chapter provides a comprehensive overview of the future of performance management, offering actionable strategies for organizations looking to foster a more responsive and employee-centric work culture. The move toward continuous feedback represents not just a trend but a fundamental rethinking of how performance is managed, with the potential to significantly enhance both individual and organizational success in the modern workplace

Drapes in Routine Aseptic Procedures for Environmental Sustainability (project DRAPES): a protocol for a multi-centre randomised controlled trial comparing post-operative wound complication rates following routine neutering of dogs and cats using reusable or disposable surgical drapes

BackgroundReusable surgical drapes have a lower lifetime environmental impact than disposable drapes in most cases. There is limited evidence regarding whether drape choice impacts patient outcomes including post-operative wound complications. The aim of this study is to compare wound complication rates following routine neutering surgeries in cats and dogs when reusable drapes are used as compared with disposable drapes.MethodsThe trial will be conducted as a pragmatic, multi-centre, parallel group randomised controlled trial in the UK. Dogs and cats undergoing routine neutering will be randomised to disposable or reusable drapes with all other aspects of care occurring as they usually would at the practice. The required sample size is 2,850, with 4750 animals to be recruited from up to ten practices to allow for a 40% loss to follow-up. Demographic data and details on peri-operative care will be collected at the time of surgery. Post-operative wound complications will be assessed and recorded as usual at each practice using clinical codes. The post-operative wound clinical codes and any antibiotic use within 30 days of surgery will be retrieved from the practice management software. The primary outcome that will be compared between the two groups is the rate of post-operative wound complications within 30 days of surgery which will be analysed by multivariable logistic regression with a binary outcome of wound complication (yes/no). Secondary outcomes are the prevalence of different types of complications and antibiotic use within 30 days of surgery which will be compared between the two groups by chi square analysis.DiscussionOur hypothesis is that there will be no difference in post-operative wound complication rates between disposable and reusable drapes. If the likely rate of post-surgical wound complications with reusable drapes is similar to that with disposable drapes, then veterinary clinical teams can choose the more sustainable option, confident that their patients will not be impacted by this choice.Trial registrationWe have retrospectively registered the protocol on the Open Science Framework on 14 Nov 2023 (Trial registration entry: https://doi.org/10.17605/OSF.IO/72HMA).

Antimicrobial Use in Cats in a University Veterinary Hospital in Central Italy: A Retrospective Study.

Background: Monitoring antimicrobial use is crucial for understanding current prescribing practices. Such information helps in establishing stewardship programs for effectively using antimicrobials and combating resistance to them. Objectives: This study describes how antimicrobials are prescribed at the Veterinary Teaching Hospital of the University of Pisa and compares how the internal medicine and intensive care units differ in their usage of antimicrobials. Methods: The study involved cats that were presented in the units in 2021 and 2022. Antimicrobial prescriptions were obtained via the hospital's management software (OCIROE). Results: In a population of 1164 non-surgical cats with 397 antimicrobials prescribed, the most prescribed ones were amoxicillin-clavulanic acid in the internal medicine unit and ampicillin in the intensive care unit. Twenty-five percent of all antimicrobials were Highest-Priority Critically Important Antimicrobials or Antimicrobial Advice Ad Hoc Expert Group Category B. The oral route was the main route of administration in the internal medicine unit, while parenteral was the most common route used in the intensive care unit. Most antimicrobials were prescribed to treat pathologic conditions affecting the urinary (39%), gastroenteric (21%), respiratory (13%), and integumentary (12%) systems. A diagnosis, accurate dosage, and the use of species-approved medications were recorded in the antimicrobial prescriptions. However, only 11% of these prescriptions were supported by antimicrobial susceptibility tests. Conclusions: These results suggest room for improvement, particularly in increasing the use of antimicrobial susceptibility testing to ensure more targeted antimicrobial therapy. Given the importance of antimicrobial resistance and the One Health approach, the study also highlights the need to consider the broader impact of antimicrobial use in animals, including the potential contribution to resistance in bacteria that affect both animal and human health.

Optimizing Organizational Efficiency: Strategic Requirement of Modern Industrial Asset Level Management

Asset Hierarchy Management (AHM) is not just a theoretical concept but a practical tool for optimizing operations in modern businesses, particularly in sectors with intricate infrastructures such as manufacturing, utilities, and healthcare. This research paper explores the significance of AHM in standardizing and enhancing organizational efficiency. It traces AHM's evolution, delineates its benefits, and provides strategies for implementation. By emphasizing the tangible benefits of AHM, the paper aims to instill optimism in the audience about its potential impact. The paper outlines prerequisites and steps for developing a robust asset hierarchy, stressing transparent governance and integration with technology solutions like Enterprise Asset Management (EAM) software. Furthermore, it presents a detailed framework for implementing AHM in manufacturing plants, highlighting the importance of defining clear asset categories, hierarchical levels, and relationships. By adhering to best practices and leveraging advanced tools, organizations can effectively manage assets, drive operational excellence, and achieve sustainable growth.

Impact of hospital pharmacy interventions on length of stay in hospitals: a protocol for a systematic review and meta-analysis

Background Length of stay (LOS) is an essential metric for hospital efficiency, patient outcomes and satisfaction. Studies indicate hospital pharmacy interventions positively affect LOS and other outcomes, yet results vary due to study differences. No systematic review or meta-analysis has been conducted on this topic; thus, the aim of this study is to systematically assess the effect of interventions on LOS. Methods This review will conduct a systematic search across MEDLINE, EMBASE, Cochrane Trials, Cochrane Reviews and the Cumulative Index to Nursing and Allied Health Literature to identify pertinent studies. An expert librarian will craft the search strategy, ensuring our review adheres to standard guidelines. We will use Covidence, a specialized systematic review management software, to optimize data management, the selection process and data extraction. A dedicated team of reviewers will independently evaluate titles and abstracts in duplicate, progressing to full-text examination of articles, to determine inclusion in our review and analysis. Data will be extracted by one reviewer, with independent data extraction by a second reviewer in a proportion of papers, and checking for consistency by a third. A template in Covidence will guide extraction of study, setting, participant, intervention and outcome characteristics and findings. The findings will be described narratively, and if possible given the methodological and statistical heterogeneity, meta-analysis will be undertaken. Discussion Considering the inconsistency of previous studies, this systematic review aims to clarify the potential impact of hospital pharmacy interventions on LOS. It will expand and reinforce existing knowledge, and provide detail about which intervention types have the most impact on LOS.

Leveraging Technology to Improve and Streamline Operations in the African Construction Sector: A Case-Based Approach

The advent of innovation in tools, materials and techniques has transformed the planning, management and execution of construction projects. Globally, the construction sector has been embracing digital technologies to enhance efficiency, reduce cost and ensure sustainability to overcome challenges and meet evolving demands in the industry. Using a case-based approach, this study shows instances from South Africa of how the construction process is being revolutionised through the deployment of cutting-edge technologies to improve and streamline operations. The approach provides an introductory background on how technology has affected construction with an extensive literature review providing clarifications and insights on construction activities, processes and key technological advancements, in addition to highlighting their importance. Findings from the cases revealed that the projects deployed one or more forms of project management software, such as RIB Software, Autodesk Revit, Primavera P6, Microsoft Project, Procore, and Aconex. It was further found that these deployments enhanced collaboration and communication, improved design coordination and clash detection, and enabled efficient resource allocation and project planning among stakeholders. The study concludes that construction activities play a key role in economic development. Sustainable construction practices would require the adoption and implementation of state-of-the-art technological solutions in the 4th Industrial Revolution that will aid the totality of construction management processes. As evidenced in the various projects, the effectiveness of construction management software in streamlining the construction process is a testament to the critical role of technological advancement as a driver of sustainability.

E-Library: A Total solution for Library Automation & Management Software for College Libraries in Rajasthan

E-Library: A Total solution for Library Automation & Management Software for College Libraries in Rajasthan

Energy-Efficient Industrial Internet of Things in Green 6G Networks

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data fusion can be carried out in energy-efficient IoT smart industrial urban environments by cooperative perception and inference tasks. Our analyses debate on 6G wireless communication, vehicular IoT intelligent and autonomous networks, and energy-efficient algorithm and green computing technologies in smart industrial equipment and manufacturing environments. Mobile edge and cloud computing task processing capabilities of decentralized network control and power grid system monitoring were thereby analyzed. Our results and contributions clarify that sustainable energy efficiency and green power generation together with IoT decision support and smart environmental systems operate efficiently in distributed artificial intelligence 6G pervasive edge computing communication networks. PRISMA was used, and with its web-based Shiny app flow design, the search outcomes and screening procedures were integrated. A quantitative literature review was performed in July 2024 on original and review research published between 2019 and 2024. Study screening, evidence map visualization, and data extraction and reporting tools, machine learning classifiers, and reference management software were harnessed for qualitative and quantitative data, collection, management, and analysis in research synthesis. Dimensions and VOSviewer were deployed for data visualization and analysis.

AUTOMATION IMPROVEMENT FOR GIS-BASED APPLICATIONS DEPLOYMENT IN FAST GROWING HIGH SCALABILITY DATA-ROOMS

This paper presents the viability and importance of automation in deploying and managing software systems to reduce costs. Automation allows for optimizing time spent on resource deployment and configuration and simplifying the upgrade process. A real-world geographic information system (GIS) project illustrates these improvements by automating WGS84 & STEREO70 conversion modules for software systems.

Comparative Analysis of Traditional Wealth Management Services vs. AI-Based Wealth Management Software

The integration of artificial intelligence (AI) is transforming the wealth management industry. This paper compares traditional wealth management with AI-based solutions to assess their value to customers, focusing on factors like cost, customization, accessibility, performance, and accuracy. Traditional wealth management offers personalized human interaction, expert advice, and tailored financial planning but often comes with higher costs and limited scalability. In contrast, AI-based wealth management uses advanced algorithms and data analytics for scalable, efficient, and cost-effective services, though it may lack the personal touch of human advisors. The study finds that traditional wealth management excels in comprehensive planning and trust-based relationships, crucial for clients with complex needs. AI-driven solutions enhance accessibility and affordability, providing sophisticated insights to a wider audience. However, concerns about personalization quality and data reliance remain. The research suggests that a hybrid model combining traditional and AI-based approaches may offer the best solution, leveraging AI’s efficiency while maintaining personalized service and expert advice. Overall, this paper provides valuable insights for financial planners, identifying strategies to enhance value in the evolving wealth management field. Keywords: Wealth Management, Artificial Intelligence (AI), Financial Planning, AI-based Solutions, Personalized Financial Advice, Hybrid Wealth Management.

Meeting Social Needs in a Crisis Context: Lessons Learned from Integrating the 'Take Care Initiative' into New York City's Testing and Contact Tracing Program.

The COVID-19 pandemic highlighted the importance of addressing social needs in a crisis context. Some US jurisdictions integrated a social service component into case investigation and contact tracing (CI/CT) programs, including the New York City (NYC) Test & Trace (T2) Program; the Take Care initiative referred NYC residents who tested positive or were exposed to COVID-19 to services to support isolation and quarantine and meet basic needs. More research is needed to determine effective implementation strategies for integrating social needs provision into CI/CT programs. To identify barriers and facilitators to the implementation of the Take Care initiative, we conducted key informant interviews with program staff, community-based organization partners, and cases and contacts as part of a larger evaluation of the T2 program. Interviews were recorded, transcribed, and analyzed using rapid qualitative methods. Key facilitators to implementation included utilizing a case management software system, employing strategies to encourage service uptake, leveraging cross-agency collaborations, and partnering with community-based organizations for resource navigation. Barriers identified included external management of the software system, challenges reaching and engaging the public, administrative complications due to shifting collaborations, and management of CBO partners' structure and hiring. Based on our findings, we provide recommendations to support effective planning and implementation of social needs service provision in a crisis context. Future research should focus on testing promising implementation strategies highlighted in this study and applying them to varied contexts and crisis situations.

A Basecamp for Student Group Projects: Analysis of the Use of Project Management Software in the Advertising, Public Relations, and Marketing Classroom

Integration of project management collaboration software has been suggested for group experiential project courses in advertising, public relations (PR), marketing, and strategic communications. But little research has been conducted on using these tools. This study sought to gauge student perceptions toward the use of project management collaboration software Basecamp on improved experience in group projects, team collaboration, and learning outcomes. A survey of 177 students in seven course sections across two semesters at two universities reveals that most students agree project management and collaboration software is a valuable learning tool. Suggestions for course and program implementation and the self-directed learning model are considered.

Impact of Biological Sex on Emotional Perception Among Adults With Schizophrenia Spectrum Disorders: Protocol for a Systematic Review.

It is well established that individuals with schizophrenia experience deficits in emotional perception that can impact long-term social and occupational functioning. Understanding the factors that impact these impairments is important for targeting interventions to improve recovery. In the general population, compared with males, females tend to show greater perception of emotions. Whether this sex difference persists in schizophrenia is less clear. In contrast to males, females diagnosed with schizophrenia tend to have a higher age of disease onset and better premorbid functioning but do not necessarily have better outcomes. Effective treatments for social cognitive impairments are highly relevant to long-term functional rehabilitation. A greater understanding of the cognitive deficits in emotional perception within females and males living with schizophrenia may assist interventions to be better tailored to individuals. This systematic review aims to collate, synthesize, and critically appraise evidence considering the influence of biological sex (female and male) on the emotional perception of individuals with schizophrenia. This is a systematic review protocol based on the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) guidelines. The electronic databases MEDLINE, Embase, CENTRAL, CINAHL, and PsycINFO will be systematically searched. To be included in this review, studies must compare the emotional perceptions of male and female participants older than 18 years who have a primary diagnosis of a schizophrenia spectrum disorder. Qualitative studies, case reports, case series, unpublished manuscripts, and studies not reported in English will be excluded. Key search strategies will include combinations of the following terms: "men," "male," "man," "female," "women," "woman," "sex," "gender," "emotional perception," "emotional processing," "schizophrenia," "schizophren," "psychotic disorders," "psychosis," "psychoses," "psychotic," "schizoaffective," "schizotypal personality disorder," and "schizotyp." Identified studies will be uploaded to the web-based Covidence systematic review management software. The risk of bias for individual studies will be assessed using the relevant Joanna Briggs Institute checklist tools. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) system will also be used to evaluate the strength of the evidence base. Findings will be synthesized to provide a systematic summary of the existing literature. If sufficiently comparable data to permit meta-analysis emerges, a random-effects meta-analysis will be performed. This systematic review was registered with the PROSPERO (International Prospective Register of Systematic Reviews) in October 2023. The search and screening of study titles and abstracts are currently underway. Data are expected to be extracted and analyzed in July 2024. Results will contribute to an improved understanding of the social cognitive profiles of males and females with schizophrenia. This knowledge is expected to inform the adaptation of interventions to improve functional outcomes. PROSPERO CRD42023463561; https://tinyurl.com/34sr3rnf. DERR1-10.2196/56977.

Fine-grained vulnerability detection for medical sensor systems

The Internet of Things (IoT) has revolutionized the healthcare system by connecting medical sensors to the internet, while also posing challenges to the security of medical sensor networks (MSN). Given the extreme sensitivity of medical data, any vulnerability may result in data breaches and misuse, impacting patient safety and privacy. Therefore, safeguarding MSN security is critical. As medical sensor devices rely on smart healthcare software systems for data management and communication, precisely detecting system code vulnerabilities is essential to ensuring network security. Effective software vulnerability detection targets two key objectives: (i) achieving high accuracy and (ii) directly identifying vulnerable code lines for developers to fix. To address these challenges, we introduce Vulcoder, a novel vulnerability-oriented, encoder-driven model based on the Bidirectional Encoder Representations from Transformers (BERT) architecture. We propose a one-to-one mapping function to capture code semantics through abstract syntax trees (AST). Combined with multi-head attention, Vulcoder achieves precise function- and line-level detection of software vulnerabilities in MSN. This accelerates the vulnerability remediation process, thereby strengthening network security. Experimental results on various datasets demonstrate that Vulcoder outperforms previous models in identifying vulnerabilities within MSN. Specifically, it achieves a 1%–419% improvement in function-level prediction F1 scores and a 12.5%–380% increase in line-level localization precision. Therefore, Vulcoder helps enhance security defenses and safeguard patient privacy in MSN, facilitating the development of smart healthcare.

Data Management System and Software for Comprehensive Assessment of the State of the Biosphere

Data Management System and Software for Comprehensive Assessment of the State of the Biosphere

Herd–level risk factors associated with preweaning mortality on Ontario dairy farms

The objective of this cross-sectional, herd-level study was to identify associations between calf management practices and herd-level preweaning mortality on Ontario dairy farms. From April to August 2022, a convenience sample of 100 dairy farms from Ontario, Canada, were visited once. A questionnaire, covering farm biosecurity, calving, colostrum management, preweaning nutrition, and housing, was verbally administered at each farm visit. Furthermore, data regarding preweaning calf mortality were retrieved from each farm's herd management software or records, including the total count of calves that survived, were culled, or died during the preweaning period for the 365 d before the farm visit. Preweaning mortality was defined as the proportion of calves that died between ≥48 h and 60 d of age divided by the total number of calves alive after 48 h of age. The herd-level preweaning mortality risk on sampled farms ranged from 0 to 15.9%, with an average of 2.8% (SD = 3.8%). A multivariable Poisson regression model was used to evaluate associations between 22 explanatory variables and preweaning mortality. Factors associated with greater herd-level preweaning mortality were larger herd size; having treatment protocols for diarrhea, pneumonia or navel infection written in collaboration with a veterinarian (compared with farms with the same treatment protocols developed without a veterinarian), and the herd-veterinarian never inquiring about calf health (compared with farms where the herd veterinarian inquired sometimes). Factors associated with lower herd-level preweaning mortality were using the calving pen for sick cows, having more than 4 people working with calves, offering calves a minimum volume of ≥9 L of milk/day, and farmers with a level of formal education higher than secondary school. These results indicate that producers may be able to reduce preweaning calf mortality by providing adequate labor for calf care, offering calves sufficient volumes of milk, being proactive in communicating with their veterinary practitioners about calf health, and potentially by engaging in continuous education.

Ichor: A Python library for computational chemistry data management and machine learning force field development.

We present ichor, an open-source Python library that simplifies data management in computational chemistry and streamlines machine learning force field development. Ichor implements many easily extensible file management tools, in addition to a lazy file reading system, allowing efficient management of hundreds of thousands of computational chemistry files. Data from calculations can be readily stored into databases for easy sharing and post-processing. Raw data can be directly processed by ichor to create machine learning-ready datasets. In addition to powerful data-related capabilities, ichor provides interfaces to popular workload management software employed by High Performance Computing clusters, making for effortless submission of thousands of separate calculations with only a single line of Python code. Furthermore, a simple-to-use command line interface has been implemented through a series of menu systems to further increase accessibility and efficiency of common important ichor tasks. Finally, ichor implements general tools for visualization and analysis of datasets and tools for measuring machine-learning model quality both on test set data and in simulations. With the current functionalities, ichor can serve as an end-to-end data procurement, data management, and analysis solution for machine-learning force-field development.

Innovative financial strategies for achieving cost reduction and revenue growth in non-profit organizations

Non-profit organizations operate in a challenging financial environment, requiring innovative strategies to ensure sustainability and maximize their impact. This review paper explores essential financial strategies for non-profits, focusing on cost reduction, revenue growth, strategic financial planning, and leveraging technology. Cost reduction strategies, including operational efficiency, process streamlining, and technology implementation, enable non-profits to optimize resource allocation. Revenue growth is achieved through diversifying funding sources, expanding donor bases, and adopting social enterprises and digital fundraising methods. Strategic financial planning and management, encompassing robust financial plans, regular audits, and risk management, are foundational for financial health. Leveraging technology, such as financial management software, data analytics, and blockchain, further enhances financial efficiency and transparency. This comprehensive approach empowers non-profits to achieve financial stability, improve resource management, and enhance their mission-driven impact. Future directions recommend exploring new financial management practices and technologies to maintain competitiveness and sustainability in an evolving landscape.

Design and development of a motion activated internet protocol video surveillance system for crowd monitoring

Internet Protocol (IP) cameras are powerful tools in security and crowd monitoring implementation owing to their efficient communication over a wide geographical area. However, for any authorized personnel to initiate recording based on an event, to report a security breach, or even to stop recording when an uninteresting scene is presented, such would have to sit at the reach of the control which is not always possible. In this proposal, we implement a motion activated internet protocol (MAIP) based video surveillance system using network video management for crowd monitoring. The system can activate itself to initiate video recording on detecting motion or event using its in-built features of the network cameras and Video Management Software (VMS). The system will result in an effective and efficient motion detection video surveillance with necessary features that allow for quick recording, conserved bandwidth, greater storage, space conservation, reduces CPU load on recording servers and also allows for integration with other systems.

Coping mechanisms and strategies adopted to improve the quality and timeliness of immunization data among lower-level private-for-profit service providers in Kampala Capital City, Uganda.

Lower-level urban private-for-profit health service providers are actively engaged in the delivery of immunization services. However, not much is known about their everyday endeavours to improve data quality and ensure the submitted data meets the quality and timeliness requirements as per established guidelines. The objective of this paper was to examine the coping mechanisms and strategies adopted to improve the quality and timeliness of immunization data among lower-level private-for-profit service providers in Kampala Capital City, Uganda. A qualitative study design was adopted with in-depth interviews (n = 17) and key informant interviews (n = 8) completed among frontline health workers, district health managers and immunization implementing partners. Analysis followed a thematic approach with coding conducted using Atlas. ti, a qualitative data management software. Overall, coping mechanisms and strategies adopted to improve the data quality among lower-level urban private-for-profit immunization service providers included; Experiential attachment for practical skills acquisition in data management, data quality peer-to-peer learning among private-for-profit immunization service providers, registration using cohort system for easy tracking of records during subsequent visits, separation of visiting service user records from regular attendants, service delivery modifications such as reward for better performance, engagement of Village Health Teams (VHTs) in outreaches and data completion, and data quality checks through review of monitoring charts to identify gaps in data quality. Within the urban context, the delivery of immunization services by lower-level private-for-profit services faces data quality challenges some of which stem from the implementation context. Different coping strategies focusing on frontline health worker skills, enhanced experience sharing through peer-to-peer learning, modifications to registration and routine review of monitoring charts. However, these efforts were often faced with chronic barriers such as the high staff turnover calling for dedicated efforts to optimize the available implementation opportunities like guidelines mandating the public health facilities to supervise the lower-level private immunization service providers within their catchment areas to respond to the identified gaps.