10,161 research outputs found

    Roles in construction projects: analysis and terminology

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    Standard form contracts are typically developed through a negotiated consensus, unless they are proffered by one specific interest group. Previously published plans of work and other descriptions of the processes in construction projects tend to focus on operational issues, or they tend to be prepared from the point of view of one or other of the dominant interest groups. Legal practice in the UK permits those who draft contracts to define their terms as they choose. There are no definitive rulings from the courts that give an indication as to the detailed responsibilities of project participants. The science of terminology offers useful guidance for discovering and describing terms and their meanings in their practical context, but has never been used for defining terms for responsibilities of participants in the construction project management process. Organizational analysis enables the management task to be deconstructed into its elemental parts in order that effective organizational structures can be developed. Organizational mapping offers a useful technique for reducing text-based descriptions of project management roles and responsibilities to a comparable basis. Research was carried out by means of a desk study, detailed analysis of nine plans of work and focus groups representing all aspects of the construction industry. No published plan of work offers definitive guidance. There is an enormous amount of variety in the way that terms are used for identifying responsibilities of project participants. A catalogue of concepts and terms (a “Terminology”) has been compiled and indexed to enable those who draft contracts to choose the most appropriate titles for project participants. The purpose of this terminology is to enable the selection and justification of appropriate terms in order to help define roles. The terminology brings an unprecedented clarity to the description of roles and responsibilities in construction projects and, as such, will be helpful for anyone seeking to assemble a team and specify roles for project participants

    Techniques for assessing the investment attractiveness of a commercial organization based on classical methods of strategic economic analysis

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    Purpose: The development of methodological support for assessing the investment attractiveness of a commercial organization, considering modern information requests of stakeholders. Design/Methodology/Approach: As part of the research, the authors have developed an algorithm for investment attractiveness assessment of a commercial organization by using the scenario method of economic analysis. Findings: It is proved that the main disadvantages of the existing methods of assessing investment attractiveness are: the lack of strategic orientation of the assessment; ignoring the influence of most external and internal factors of activity; the inability to assess the risk of investing in the analyzed object; the need to compare with the level of investment attractiveness of similar organizations for an objective interpretation of the results. Practical implications: To eliminate the significant shortcomings of modern methodological support in this area, the authors recommend the use of scenario method of strategic economic analysis in the process of assessing the investment attractiveness of the organization. Originality/Value: The scenario method of strategic economic analysis proposed by the authors complements the existing approaches with the ability to take into account potential risks when making a far-sighted decision to invest in an organization by combining the results of retrospective analysis and forecasting changes in the quantitative and qualitative characteristics of financial and economic activity.peer-reviewe

    Discrete Event Simulations

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    Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES

    Research and Applications of the Processes of Performance Appraisal: A Bibliography of Recent Literature, 1981-1989

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    [Excerpt] There have been several recent reviews of different subtopics within the general performance appraisal literature. The reader of these reviews will find, however, that the accompanying citations may be of limited utility for one or more reasons. For example, the reference sections of these reviews are usually composed of citations which support a specific theory or practical approach to the evaluation of human performance. Consequently, the citation lists for these reviews are, as they must be, highly selective and do not include works that may have only a peripheral relationship to a given reviewer\u27s target concerns. Another problem is that the citations are out of date. That is, review articles frequently contain many citations that are fifteen or more years old. The generation of new studies and knowledge in this field occurs very rapidly. This creates a need for additional reference information solely devoted to identifying the wealth of new research, ideas, and writing that is changing the field

    Quality Function Deployment in Continuous Improvement

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    Managing appointment booking under customer choices

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    Motivated by the increasing use of online appointment booking platforms, we study how to offer appointment slots to customers to maximize the total number of slots booked. We develop two models, nonsequential offering and sequential offering, to capture different types of interactions between customers and the scheduling system. In these two models, the scheduler offers either a single set of appointment slots for the arriving customer to choose from or multiple sets in sequence, respectively. For the nonsequential model, we identify a static randomized policy, which is asymptotically optimal when the system demand and capacity increase simultaneously, and we further show that offering all available slots at all times has a constant factor of two performance guarantee. For the sequential model, we derive a closed form optimal policy for a large class of instances and develop a simple, effective heuristic for those instances without an explicit optimal policy. By comparing these two models, our study generates useful operational insights for improving the current appointment booking processes. In particular, our analysis reveals an interesting equivalence between the sequential offering model and the nonsequential offering model with perfect customer preference information. This equivalence allows us to apply sequential offering in a wide range of interactive scheduling contexts. Our extensive numerical study shows that sequential offering can significantly improve the slot fill rate (6%–8% on average and up to 18% in our testing cases) compared with nonsequential offering. Given the recent and ongoing growth of online and mobile appointment booking platforms, our research findings can be particularly useful to inform user interface design of these booking platforms

    Diagnosis and Prognosis of Occupational disorders based on Machine Learn- ing Techniques applied to Occupational Profiles

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    Work-related disorders have a global influence on people’s well-being and quality of life and are a financial burden for organizations because they reduce productivity, increase absenteeism, and promote early retirement. Work-related musculoskeletal disorders, in particular, represent a significant fraction of the total in all occupational contexts. In automotive and industrial settings where workers are exposed to work-related muscu- loskeletal disorders risk factors, occupational physicians are responsible for monitoring workers’ health protection profiles. Occupational technicians report in the Occupational Health Protection Profiles database to understand which exposure to occupational work- related musculoskeletal disorder risk factors should be ensured for a given worker. Occu- pational Health Protection Profiles databases describe the occupational physician states, and which exposure the physicians considers necessary to ensure the worker’s health protection in terms of their functional work ability. The application of Human-Centered explainable artificial intelligence can support the decision making to go from worker’s Functional Work Ability to explanations by integrating explainability into medical (re- striction) and supporting in two decision contexts: prognosis and diagnosis of individual, work related and organizational risk condition. Although previous machine learning ap- proaches provided good predictions, their application in an actual occupational setting is limited because their predictions are difficult to interpret and hence, not actionable. In this thesis, injured body parts in which the ability changed in a worker’s functional work ability status are targeted. On the one hand, artificial intelligence algorithms can help technical teams, occupational physicians, and ergonomists determine a worker’s workplace risk via the diagnosis and prognosis of body part(s) injuries; on the other hand, these approaches can help prevent work-related musculoskeletal disorders by identifying which processes are lacking in working condition improvement and which workplaces have a better match between the remaining functional work abilities. A sample of 2025 for the prognosis part (from the years of 2019 to 2020) and 7857 for the prognosis part of Occupational Health Protection Profiles based on Functional Work Ability textual re- ports in the Portuguese language in automotive industry factory. Machine learning-based Natural Language Processing methods were implemented to extract standardized infor- mation. The prognosis and diagnosis of Occupational Health Protection Profiles factors were developed in reliable Human-Centered explainable artificial intelligence system to promote a trustworthy Human-Centered explainable artificial intelligence system (enti- tled Industrial microErgo application). The most suitable regression models to predict the next medical appointment for the injured body regions were the models based on CatBoost regression, with R square and an RMSLE of 0.84 and 1.23 weeks, respectively. In parallel, CatBoost’s best regression model for most body parts is the prediction of the next injured body parts based on these two errors. This information can help tech- nical industrial teams understand potential risk factors for Occupational Health Protec- tion Profiles and identify warning signs of the early stages of musculoskeletal disorders.Os transtornos relacionados ao trabalho têm influência global no bem-estar e na quali- dade de vida das pessoas e são um ônus financeiro para as organizações, pois reduzem a produtividade, aumentam o absenteísmo e promovem a aposentadoria precoce. Os distúr- bios osteomusculares relacionados ao trabalho, em particular, representam uma fração significativa do total em todos os contextos ocupacionais. Em ambientes automotivos e industriais onde os trabalhadores estão expostos a fatores de risco de distúrbios osteomus- culares relacionados ao trabalho, os médicos do trabalho são responsáveis por monitorar os perfis de proteção à saúde dos trabalhadores. Os técnicos do trabalho reportam-se à base de dados dos Perfis de Proteção da Saúde Ocupacional para compreender quais os fatores de risco de exposição a perturbações músculo-esqueléticas relacionadas com o tra- balho que devem ser assegurados para um determinado trabalhador. As bases de dados de Perfis de Proteção à Saúde Ocupacional descrevem os estados do médico do trabalho e quais exposições os médicos consideram necessária para garantir a proteção da saúde do trabalhador em termos de sua capacidade funcional para o trabalho. A aplicação da inteligência artificial explicável centrada no ser humano pode apoiar a tomada de decisão para ir da capacidade funcional de trabalho do trabalhador às explicações, integrando a explicabilidade à médica (restrição) e apoiando em dois contextos de decisão: prognóstico e diagnóstico da condição de risco individual, relacionado ao trabalho e organizacional . Embora as abordagens anteriores de aprendizado de máquina tenham fornecido boas pre- visões, sua aplicação em um ambiente ocupacional real é limitada porque suas previsões são difíceis de interpretar e portanto, não acionável. Nesta tese, as partes do corpo lesiona- das nas quais a habilidade mudou no estado de capacidade funcional para o trabalho do trabalhador são visadas. Por um lado, os algoritmos de inteligência artificial podem aju- dar as equipes técnicas, médicos do trabalho e ergonomistas a determinar o risco no local de trabalho de um trabalhador por meio do diagnóstico e prognóstico de lesões em partes do corpo; por outro lado, essas abordagens podem ajudar a prevenir distúrbios muscu- loesqueléticos relacionados ao trabalho, identificando quais processos estão faltando na melhoria das condições de trabalho e quais locais de trabalho têm uma melhor correspon- dência entre as habilidades funcionais restantes do trabalho. Para esta tese, foi utilizada uma base de dados com Perfis de Proteção à Saúde Ocupacional, que se baseiam em relató- rios textuais de Aptidão para o Trabalho em língua portuguesa, de uma fábrica da indús- tria automóvel (Auto Europa). Uma amostra de 2025 ficheiros foi utilizada para a parte de prognóstico (de 2019 a 2020) e uma amostra de 7857 ficheiros foi utilizada para a parte de diagnóstico. . Aprendizado de máquina- métodos baseados em Processamento de Lingua- gem Natural foram implementados para extrair informações padronizadas. O prognóstico e diagnóstico dos fatores de Perfis de Proteção à Saúde Ocupacional foram desenvolvidos em um sistema confiável de inteligência artificial explicável centrado no ser humano (inti- tulado Industrial microErgo application). Os modelos de regressão mais adequados para prever a próxima consulta médica para as regiões do corpo lesionadas foram os modelos baseados na regressão CatBoost, com R quadrado e RMSLE de 0,84 e 1,23 semanas, res- pectivamente. Em paralelo, a previsão das próximas partes do corpo lesionadas com base nesses dois erros relatados pelo CatBoost como o melhor modelo de regressão para a mai- oria das partes do corpo. Essas informações podem ajudar as equipes técnicas industriais a entender os possíveis fatores de risco para os Perfis de Proteção à Saúde Ocupacio- nal e identificar sinais de alerta dos estágios iniciais de distúrbios musculoesqueléticos
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