Para permitir um efetivo gerenciamento de processos de negócio, o primeiro passo é o desenvolvimento de modelos de processo adequados aos objetivos das organizações. Tais modelos são utilizados para descreverem papéis e responsabilidades dos colaboradores nas organizações. Além disso, a modelagem de processos é de grande importância para documentar, entender e automatizar processos. As organizações, geralmente provêm documentos não estruturados e de difícil entendimento por parte dos analistas. Neste panorama, a modelagem de processos se torna demorada e de alto custo, podendo gerar modelos de processo que estão em desacordo com a realidade prevista pelas organizações. A extração de modelos ou fragmentos de processo a partir de descrições textuais pode contribuir para minimizar o esforço necessário à modelagem de processos. Neste contexto, esta dissertação propõe uma abordagem para identificar elementos de processo de negócio em texto em linguagem natural de forma semiautomática. Baseado no estudo de processamento de linguagem natural, foi definido um conjunto de regras de mapeamento para identificar elementos de processo em descrição textual Além disso, para avaliar as regras de mapeamento e viabilizar a abordagem proposta, foi desenvolvido um protótipo capaz de identificar elementos de processo em texto de forma semiautomática. Para medir o desempenho do protótipo proposto, foram utilizadas métricas de recuperação de informação, tais como precisão, revocação e medida-F. Além disso, foram aplicados dois questionários com o objetivo de verificar a aceitação perante os usuários. As avaliações apresentam resultados promissores. A análise de 70 textos, apresentou, em média, 73,61% de precisão, 70,15% de revocação e 71,82% de medida-F. Além disso, os resultados do primeiro e segundo questionários apresentaram, em média, 91,66% de aceitação dos participantes. A principal contribuição deste trabalho é propor regras de mapeamento para identificar elementos de processo em texto em linguagem natural para auxiliar e minimizar o tempo necessário à modelagem de processos realizada pelos analistas de processo. / To enable effective business process management, the first step is the design of appropriate process models to the organization’s objectives. These models are used to describe roles and responsibilities of the employees in an organizations. In addition, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. In this context, process modeling becomes highly time consuming and expensive, generating process models that do not comply with the reality of the organizations. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this dissertation proposes a semi-automatic approach to identify process elements in natural language text. Based on the study of natural language processing, it was defined a set of mapping rules to identify process elements in text. In addition, in order to evaluate the mapping rules and to demonstrate the feasibility of the proposed approach, a prototype was developed able to identify process elements in text in a semiautomatic way To measure the performance of the proposed prototype metrics were used to retrieve information such as precision, recall, and F-measure. In addition, two surveys were developed with the purpose of verifying the acceptance of the users. The evaluations present promising results. The analyses of 70 texts presented, on average, 73.61% precision, 70.15% recall and 71.82% F-measure. In addition, the results of the first and second surveys presented on average 91.66% acceptance of the participants. The main contribution of this work is to provide mapping rules for identify process elements in natural language text to support and minimize the time required for process modeling performed by process analysts.

Para permitir um efetivo gerenciamento de processos de negócio, o primeiro passo é o desenvolvimento de modelos de processo adequados aos objetivos das organizações. Tais modelos são utilizados para descreverem papéis e responsabilidades dos colaboradores nas organizações. Além disso, a modelagem de processos é de grande importância para documentar, entender e automatizar processos. As organizações, geralmente provêm documentos não estruturados e de difícil entendimento por parte dos analistas. Neste panorama, a modelagem de processos se torna demorada e de alto custo, podendo gerar modelos de processo que estão em desacordo com a realidade prevista pelas organizações. A extração de modelos ou fragmentos de processo a partir de descrições textuais pode contribuir para minimizar o esforço necessário à modelagem de processos. Neste contexto, esta dissertação propõe uma abordagem para identificar elementos de processo de negócio em texto em linguagem natural de forma semiautomática. Baseado no estudo de processamento de linguagem natural, foi definido um conjunto de regras de mapeamento para identificar elementos de processo em descrição textual Além disso, para avaliar as regras de mapeamento e viabilizar a abordagem proposta, foi desenvolvido um protótipo capaz de identificar elementos de processo em texto de forma semiautomática. Para medir o desempenho do protótipo proposto, foram utilizadas métricas de recuperação de informação, tais como precisão, revocação e medida-F. Além disso, foram aplicados dois questionários com o objetivo de verificar a aceitação perante os usuários. As avaliações apresentam resultados promissores. A análise de 70 textos, apresentou, em média, 73,61% de precisão, 70,15% de revocação e 71,82% de medida-F. Além disso, os resultados do primeiro e segundo questionários apresentaram, em média, 91,66% de aceitação dos participantes. A principal contribuição deste trabalho é propor regras de mapeamento para identificar elementos de processo em texto em linguagem natural para auxiliar e minimizar o tempo necessário à modelagem de processos realizada pelos analistas de processo. / To enable effective business process management, the first step is the design of appropriate process models to the organization’s objectives. These models are used to describe roles and responsibilities of the employees in an organizations. In addition, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. In this context, process modeling becomes highly time consuming and expensive, generating process models that do not comply with the reality of the organizations. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this dissertation proposes a semi-automatic approach to identify process elements in natural language text. Based on the study of natural language processing, it was defined a set of mapping rules to identify process elements in text. In addition, in order to evaluate the mapping rules and to demonstrate the feasibility of the proposed approach, a prototype was developed able to identify process elements in text in a semiautomatic way To measure the performance of the proposed prototype metrics were used to retrieve information such as precision, recall, and F-measure. In addition, two surveys were developed with the purpose of verifying the acceptance of the users. The evaluations present promising results. The analyses of 70 texts presented, on average, 73.61% precision, 70.15% recall and 71.82% F-measure. In addition, the results of the first and second surveys presented on average 91.66% acceptance of the participants. The main contribution of this work is to provide mapping rules for identify process elements in natural language text to support and minimize the time required for process modeling performed by process analysts.

Para permitir um efetivo gerenciamento de processos de negócio, o primeiro passo é o desenvolvimento de modelos de processo adequados aos objetivos das organizações. Tais modelos são utilizados para descreverem papéis e responsabilidades dos colaboradores nas organizações. Além disso, a modelagem de processos é de grande importância para documentar, entender e automatizar processos. As organizações, geralmente provêm documentos não estruturados e de difícil entendimento por parte dos analistas. Neste panorama, a modelagem de processos se torna demorada e de alto custo, podendo gerar modelos de processo que estão em desacordo com a realidade prevista pelas organizações. A extração de modelos ou fragmentos de processo a partir de descrições textuais pode contribuir para minimizar o esforço necessário à modelagem de processos. Neste contexto, esta dissertação propõe uma abordagem para identificar elementos de processo de negócio em texto em linguagem natural de forma semiautomática. Baseado no estudo de processamento de linguagem natural, foi definido um conjunto de regras de mapeamento para identificar elementos de processo em descrição textual Além disso, para avaliar as regras de mapeamento e viabilizar a abordagem proposta, foi desenvolvido um protótipo capaz de identificar elementos de processo em texto de forma semiautomática. Para medir o desempenho do protótipo proposto, foram utilizadas métricas de recuperação de informação, tais como precisão, revocação e medida-F. Além disso, foram aplicados dois questionários com o objetivo de verificar a aceitação perante os usuários. As avaliações apresentam resultados promissores. A análise de 70 textos, apresentou, em média, 73,61% de precisão, 70,15% de revocação e 71,82% de medida-F. Além disso, os resultados do primeiro e segundo questionários apresentaram, em média, 91,66% de aceitação dos participantes. A principal contribuição deste trabalho é propor regras de mapeamento para identificar elementos de processo em texto em linguagem natural para auxiliar e minimizar o tempo necessário à modelagem de processos realizada pelos analistas de processo. / To enable effective business process management, the first step is the design of appropriate process models to the organization’s objectives. These models are used to describe roles and responsibilities of the employees in an organizations. In addition, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. In this context, process modeling becomes highly time consuming and expensive, generating process models that do not comply with the reality of the organizations. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this dissertation proposes a semi-automatic approach to identify process elements in natural language text. Based on the study of natural language processing, it was defined a set of mapping rules to identify process elements in text. In addition, in order to evaluate the mapping rules and to demonstrate the feasibility of the proposed approach, a prototype was developed able to identify process elements in text in a semiautomatic way To measure the performance of the proposed prototype metrics were used to retrieve information such as precision, recall, and F-measure. In addition, two surveys were developed with the purpose of verifying the acceptance of the users. The evaluations present promising results. The analyses of 70 texts presented, on average, 73.61% precision, 70.15% recall and 71.82% F-measure. In addition, the results of the first and second surveys presented on average 91.66% acceptance of the participants. The main contribution of this work is to provide mapping rules for identify process elements in natural language text to support and minimize the time required for process modeling performed by process analysts.

Durant l’exploitation d’une ligne de métro, l’opérateur de supervision est responsable de l’exécution de procédures pour la gestion des incidents. Cependant, lors de l’occurrence combinée d’incidents, les procédures utilisées peuvent se retrouver en concurrence. Dans ce cas, des situations ne garantissant pas la sécurité des personnes existent et un accident peut se déclencher. La démarche d’étude des procédures intègre tout d’abord leur représentation graphique avec la notation BPMN. Ces modèles de procédure, compréhensibles et accessibles, constituent ainsi une base de connaissances pour les industriels concernés. Ces modèles sont ensuite interprétés sous forme de réseaux de Petri pour ajouter une dynamique au système étudié. La notion de contrôlabilité et l’influence du contexte d’exécution sont alors introduites dans l’étude de procédures de gestion d’incident. Afin d’assurer la sécurité des personnes, des états interdits sont définis et identifiés parmi l’ensemble des états accessibles par l’application de la théorie du contrôle par supervision. Ces états interdits se caractérisent de manière originale : suivant leur inclusion dans un ensemble d’états particuliers mais également suivant la contrôlabilité de leurs transitions sortantes. Cette caractérisation innovante s’accompagne des algorithmes permettant de déterminer et d’éviter les états interdits. Afin d’orienter l’opérateur de supervision dans les actions à exécuter lors d’incidents combinés, des critères de différenciation des trajectoires admissibles évitant les états interdits sont également définis. Les résultats obtenus permettent de proposer une assistance à l’opérateur de supervision sous forme d’alertes et de conseils. Cette étude se base sur le système de supervision ATS développé par Thales et sur les procédures de gestion d’incident de l’un de leurs clients, la RATP. Un prototype de fonctionnalité d’aide à l’opérateur pour la gestion des incidents reposant sur le savoir-faire client a ainsi pu être intégré au logiciel de Thales. / During metro line operations, the supervision operator is responsible for the procedures’ execution when referring to incidents management. However, when combined incidents occur, procedures may be competing. In this particular case, situations which do not ensure people’s safety exist and an accident might happen. Firstly, the approach of studying these procedures integrates their graphical representation with the BPMN notation. These procedures’ models, understandable and accessible, provide a significant amount of knowledge for industrials in this area. Secondly, these models are performed as Petri nets to add dynamic to the system of interest. That is why, the notion of controllability and the influence of the execution context are introduced in the study of incidents management procedures. To ensure people’s safety, forbidden states are defined and identified among the states space with the supervisory control theory. These states are characterized in an original way : depending on their inclusion in a set of states but also depending on the controllability of their outgoing transitions. In addition to this innovative characterization, algorithms allow to determine and to avoid forbidden states. Criteria distinguish the admissible sequences which avoid forbidden states. These differentiation criteria are defined to steer the supervision operator through the actions he has to execute when combined incidents occur. Results allow us to provide assistance to the supervision operator with warnings and advice. This study is based on ATS supervision system developed by Thales and one of their customers’ incidents management procedures, the RATP. A prototype of operator support functionality for incidents management based on customer know-how has been implemented into Thales software.

Sustainability including the reporting requirements is one of the most relevant topics for companies. In recent years, many software providers have launched new software tools targeting companies committed to implementing sustainability reporting. But it’s not only companies willing to use their Business Intelligence (BI) solution, there are also basic principles such as the single source of truth and tendencies to combine sustainability reporting with the financial reporting (Integrated Reporting) The IT integration of sustainability reporting has received limited attention by scientific research and can be facilitated using BI systems. This has to be done both to anticipate the economic demand for integrated reporting from an IT perspective as well as for ensuring the reporting of revisable data. Through the adaption of BI systems, necessary environmental and social changes can be addressed rather than merely displaying sustainability data from additional, detached systems or generic spreadsheet applications. This thesis presents research in the two domains sustainability reporting and Business Intelligence and provides a method to support companies willing to implement sustainability reporting with BI. SureBI presented within this thesis is developed to address experts from both sustainability and BI. At first BI is researched from a IT and project perspective and a novel BI reporting process is developed. Then, sustainability reporting is researched focusing on the reporting content and a sustainability reporting process is derived. Based on these two reporting processes SureBI is developed, a step-by-step process method, aiming to guide companies through the process of implementing sustainability reporting using their BI environment. Concluding, an evaluation and implementation assesses the suitability and correctness of the process model and exemplarily implements crucial IT tasks of the process. The novel combination of these two topics indicates challenges from both fields. In case of BI, users face problems regarding historically grown systems and lacking implementation strategies. In case of sustainability, the mostly voluntary manner of this reporting leads to an uncertainty as to which indicators have to be reported. The resulting SureBI addresses and highlights these challenges and provides methods for the addressing and prioritization of new stakeholders, the prioritization of the reporting content and describes possibilities to integrate the high amount of estimation figures using BI. Results prove that sustainability reporting could and should be implemented using existing BI solutions.

Since China embraced the “Open Door” policy in 1978, innovation has been an increasingly important factor for the Chinese economy. China is now the third largest country in the world league table of patent applications. China has also received large amounts of foreign direct investment, much of it from major Western innovative companies. In the earlier years of the Open Door policy, much of the involvement of Western companies was through joint ventures. International joint ventures are still important, and it is believed have substantially enhanced China's innovative capability. It is the contention of this research that there is a direct correlation between the arrivals of Sino-Western JVs and China's increased innovation capabilities. This is an important area of study as China moves towards becoming a developed economy. The gap in research at present is in applying innovation theory to China and to JVs. The thesis explores the contribution of Sino-Western JVs to the development of China's innovative capabilities. A model of the innovation process is developed, and eight important factors that are considered to enhance a company's innovative capacity, are derived from the model. The factors, expressed as propositions, are: 1: Becoming part of a wide innovative network in its industry 2: Taking part in an open innovation system in its industry 3: Relating closely to universities, and particularly their research laboratories 4: Relating closely to research institutions 5: Developing a social atmosphere conducive to innovation 6: Developing a strong strategic planning system with innovation as a focus 7: Having innovation as a primary objective of both partners at the outset of the joint venture 8: Focusing on developing intellectual property To investigate whether these propositions were accepted by Sino-Western joint ventures, 40 semi-structured interviews were conducted in ten international (Sino-western) joint ventures in China. In general the interviews provided support for the propositions. However, some reservations were expressed. Executives were reluctant to engage in open (collaborative) innovation, preferring to seek patents for developed intellectual property. They also perceived the main objective of the Western partners to be commercial success rather than innovation, although the Chinese partners were very much innovation-orientated. The research contributes to our understanding of the contribution of Sino-western JVs to the innovative capability of Chinese companies, and provides support for most of the propositions identified in the literature. Respondents remarked that most of the propositions would apply also to self-standing companies in China, and suggested that joint ventures could stimulate innovation in indigenous Chinese companies. In addition to providing a historical overview of the development of innovation in China, developing an innovation process model and testing it in the Chinese context, the thesis makes important policy and practical recommendations to Chinese organizations.

Caregiving can be stressful, and older adults’ health and well-being may be impacted by the roles and responsibilities they assume as caregivers for persons with serious mental illness (SMI). This study is the first to apply the Stress Process Model of Caregiving (SPM) in an attempt to understand how mental illness stigma influences caregiver outcomes, specifically their desire to relinquish care. The intent of this study was to call attention to care relinquishment as an under-studied stress process outcome and to explore stress factors, with a focus on mental illness stigma, that contribute to SMI caregivers’ desire to relinquish care. Using convenience sampling, members of the National Alliance on Mental Illness in the eastern U.S. were invited to participate in an online survey, resulting in a sample of n = 285. Regression analysis findings suggest that caregivers’ partnership status, exposure to problematic behaviors, and perceptions of courtesy stigma predicted desire to relinquish care. Neither age nor caregiver sense of mastery moderated the relationship between perceived courtesy stigma and relinquishment desire. Perceptions of stigma were negatively associated with caregiver health, sense of mastery, and social support levels, indicating stigma’s role in the erosion of caregiver resources. This study provides information that can inform the development of educational and supportive services that may help caregivers better cope with the stressors associated with SMI caregiving. With caregiving stressors diminished, older caregivers will be able to better apply their resources toward self-care and maintaining their quality of life.

Process model matchers automate the detection of activities that represent similar functionality in different models. Thus, they provide support for various tasks related to the management of business processes including model collection management and process design. Yet, prior research primarily demonstrated the matchers’ effectiveness, i.e., the accuracy and the completeness of the results. In this context (i) the size of the empirical data is often small, (ii) all data is used for the matcher development, and (iii) the validity of the design decisions is not studied. As a result, existing matchers yield a varying and typically low effectiveness when applied to different datasets, as among others demonstrated by the process model matching contests in 2013 and 2015. With this in mind, the thesis studies the effectiveness of matchers by separating development from evaluation data and by empirically analyzing the validity and the limitations of design decisions. In particular, the thesis develops matchers that rely on different sources of information. First, the activity labels are considered as natural-language descriptions and the Bag-of-Words Technique is introduced which achieves a high effectiveness in comparison to the state of the art. Second, the Order Preserving Bag-of-Words Technique analyzes temporal dependencies between activities in order to automatically configure the Bag-of-Words Technique and to improve its effectiveness. Third, expert feedback is used to adapt the matchers to the domain characteristics of process model collections. Here, the Adaptive Bag-of-Words Technique is introduced which outperforms the state-of-the-art matchers and the other matchers from this thesis.

The internet has become an important social context in adolescence, and communicating online with friends has become a natural part of everyday life. The present cross-sectional study examined the effects of social cues and popularity on developing adolescent social cognitions in online settings using a sample of 90, 11- to 14-year-old students from British Columbia, Canada. Participants completed self-report cyber-bullying, cyber-victimization, and cyber-aggression motivation measures. Hostile intent attributions were obtained using an instrument containing 8 hypothetical vignettes, where potentially harmful messages were sent to the protagonist, but the sender’s intentions were ambiguous. The results show an increasing cyber-bullying and cyber-victimization trend from early- to mid- adolescence. There was some evidence to suggest that individuals in mid-adolescence were more sensitive to online social cues and popularity. Individuals in mid-adolescence were more likely to engage in cyber-aggressive behavior to obtain a material or social reward. Despite having a small sample size, this study provides a good foundation for further research examining developmental processes that underlie cyberbullying behavior. / Graduate

With increasing demands from customers, companies face the challenges of shortening the new product development (NPD) period, reducing development cost and increasing development efficiency. High quality and efficiency of NPD can increase the chance for companies to be competitive on the market. Forming up cross-functional teams becomes a popular way of maximizing the knowledge then increase the development quality and efficiency. However, it is challenging to integrate the resources from different functions and even more challenging when the resources are from different countries. To overcome the integration challenges can increase the efficiency of NPD projects therefore finally win global market shares. This study’s purpose is to identify and analyze integration challenges experienced by a verification team involved in global NPD and to suggest how those challenges can be managed by answering two research questions: 1) What are the integration challenges with the current work process encountered by the global verification team? 2) How can the integration challenges be met in the improved work process? The case study is used as the research method in order to get deep insight of the challenges that a global verification team faces. VSM Group AB, an international leading sewing company is selected as the case company.  The case team, a global verification team locates both in Sweden and China, plays the role of verification work within NPD process. The case team verifies the design and new products in the process.  Through interviews, observation and literature reviews, the challenges in this global verification team are identified. It is found that the case team needs to overcome language barriers, culture difference, task planning and formalization and standardization on work performance during integration. Based on the investigations, a set of solutions are proposed in the end to meet the challenges. These solutions are an improved work process, work performance system, training program and uniformed documentation. These proposals are inspired by the integration mechanisms such as formalization and standardization, special reports etc and then fit them into the case team context. By simulation and evaluation the solutions within the global verification team, the feedback on the proposals helped for improvement. This case study at VSM is an empirical example of implementation of integration mechanisms into a real life context.