Road transports face increasing societal challenges with respect to emissions, safety, and traffic congestion, as well as business challenges. Truck automation, e.g. self-driving trucks may be utilized to address some of these issues. Autonomous transport vehicles may be characterized as Cyber-Physical Systems (CPS). A drawback is that CPS significantly increase technical complexity and thus introduce new challenges to system architecting. A product architecture is the interrelation between physical components and their function, i.e. their purpose. Product architectures can be categorized as being modular or integral. The main purpose of a modular architecture is to enable external variety and at the same time internal commonality. Products with a modular architecture are configured from predesigned building blocks, i.e. modules. A stable module, which is a carrier of main function(s) has standardized interfaces, is configured for company-specific reasons, which means it supports a company-specific (business) strategy. In this thesis, the present state at the heavy vehicle manufacturer Scania, concerning product architecting, modularization, product description and configuration is investigated. Moreover, a new clustering based method for product modularization that integrates product complexity and company business strategies is proposed. The method is logically verified with multiple industrial cases, where the architecture of a heavy truck driveline is used as a test bench. The driveline contains synergistic configurations of mechanical, electrical and software technologies that are constituents of an automated  and/or semi-autonomous system, i.e. the driveline may be characterized as a CPS. The architecture is analyzed both from technical complexity and business strategy point of view.  The presented research indicates that a structured methodology which supports the development of the product architecture is needed at Scania, to enable control of the increasing technical complexity in the Cyber-Physical Systems. Finally, configuration rules are identified to be highly important in order to successfully realize a modular product architecture. A drawback with this approach is that the solution space becomes hard to identify, therefore a complete and flexible product description methodology is essential. The results from the case studies indicate that clustering of a Product Architecture DSM may result in a modular architecture with significantly reduced complexity, but with clusters that contain conflicting module drivers. It is also identified that the new modularization methodology is capable of identifying and proposing reasonable module candidates that address product complexity as well as company-specific strategies. Furthermore, several case studies show that the proposed method can be used for analyzing and finding the explicit and/or implicit, technical as well as strategic, reasons behind the architecture of an existing product.

Road transports face increasing societal challenges with respect to emissions, safety, and traffic congestion, as well as business challenges. Truck automation, e.g. self-driving trucks may be utilized to address some of these issues. Autonomous transport vehicles may be characterized as Cyber-Physical Systems (CPS). A drawback is that CPS significantly increase technical complexity and thus introduce new challenges to system architecting. A product architecture is the interrelation between physical components and their function, i.e. their purpose. Product architectures can be categorized as being modular or integral. The main purpose of a modular architecture is to enable external variety and at the same time internal commonality. Products with a modular architecture are configured from predesigned building blocks, i.e. modules. A stable module, which is a carrier of main function(s) has standardized interfaces, is configured for company-specific reasons, which means it supports a company-specific (business) strategy. In this thesis, the present state at the heavy vehicle manufacturer Scania, concerning product architecting, modularization, product description and configuration is investigated. Moreover, a new clustering based method for product modularization that integrates product complexity and company business strategies is proposed. The method is logically verified with multiple industrial cases, where the architecture of a heavy truck driveline is used as a test bench. The driveline contains synergistic configurations of mechanical, electrical and software technologies that are constituents of an automated  and/or semi-autonomous system, i.e. the driveline may be characterized as a CPS. The architecture is analyzed both from technical complexity and business strategy point of view.  The presented research indicates that a structured methodology which supports the development of the product architecture is needed at Scania, to enable control of the increasing technical complexity in the Cyber-Physical Systems. Finally, configuration rules are identified to be highly important in order to successfully realize a modular product architecture. A drawback with this approach is that the solution space becomes hard to identify, therefore a complete and flexible product description methodology is essential. The results from the case studies indicate that clustering of a Product Architecture DSM may result in a modular architecture with significantly reduced complexity, but with clusters that contain conflicting module drivers. It is also identified that the new modularization methodology is capable of identifying and proposing reasonable module candidates that address product complexity as well as company-specific strategies. Furthermore, several case studies show that the proposed method can be used for analyzing and finding the explicit and/or implicit, technical as well as strategic, reasons behind the architecture of an existing product.

abstract: Mobile applications (Apps) markets with App stores have introduced a new approach to define and sell software applications with access to a large body of heterogeneous consumer population. Several distinctive features of mobile App store markets including – (a) highly heterogeneous consumer preferences and values, (b) high consumer cognitive burden of searching a large selection of similar Apps, and (c) continuously updateable product features and price – present a unique opportunity for IS researchers to investigate theoretically motivated research questions in this area. The aim of this dissertation research is to investigate the key determinants of mobile Apps success in App store markets. The dissertation is organized into three distinct and related studies. First, using the key tenets of product portfolio management theory and theory of economies of scope, this study empirically investigates how sellers’ App portfolio strategies are associated with sales performance over time. Second, the sale performance impacts of App product cues, generated from App product descriptions and offered from market formats, are examined using the theories of market signaling and cue utilization. Third, the role of App updates in stimulating consumer demands in the presence of strong ranking effects is appraised. The findings of this dissertation work highlight the impacts of sellers’ App assortment, strategic product description formulation, and long-term App management with price/feature updates on success in App market. The dissertation studies make key contributions to the IS literature by highlighting three key managerially and theoretically important findings related to mobile Apps: (1) diversification across selling categories is a key driver of high survival probability in the top charts, (2) product cues strategically presented in the descriptions have complementary relationships with market cues in influencing App sales, and (3) continuous quality improvements have long-term effects on App success in the presence of strong ranking effects. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2015

Submitted by Lenieze Lira (leniezeblira@gmail.com) on 2016-07-25T13:47:02Z No. of bitstreams: 1 Dissertação - André Luiz Lopes Porto.pdf: 14791950 bytes, checksum: be2de076023a64a02a6a43c99e9977d8 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-07-28T13:48:47Z (GMT) No. of bitstreams: 1 Dissertação - André Luiz Lopes Porto.pdf: 14791950 bytes, checksum: be2de076023a64a02a6a43c99e9977d8 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-07-28T13:50:19Z (GMT) No. of bitstreams: 1 Dissertação - André Luiz Lopes Porto.pdf: 14791950 bytes, checksum: be2de076023a64a02a6a43c99e9977d8 (MD5) / Made available in DSpace on 2016-07-28T13:50:19Z (GMT). No. of bitstreams: 1 Dissertação - André Luiz Lopes Porto.pdf: 14791950 bytes, checksum: be2de076023a64a02a6a43c99e9977d8 (MD5) Previous issue date: 2015-11-17 / In this thesis we propose a new method for extraction data in rich Web pages that uses only the textual content of these pages. Our method, called FIEX (Format Independent Web Data Extraction), is based on information extraction techniques for text segmentation, and can extract data from Web pages where methods of state of the art based on data alignment techniques fail due to inconsistency between the logical structure of Web pages and the conceptual structure of the data represented in them. The FIEX, unlike the methods previously proposed in the literature, is able to extract data using only the textual content of a Web pages in challenging scenarios such as severe cases of textual elements compounds, in which various values of interest for extraction are represented by only one HTML element. To perform the extraction data of the web pages, FIEX is based on techniques of elimination noise by information redundancy and an information extraction method for text segmentation known in the literature as ONDUX (On-Demand Unsupervised Learning for Information Extraction). In our experiments, we used various Web pages collections of di erent areas of products and e-commerce stores with goal to extract data from product descriptions. The choose of this type of Web page, due to the large amount of data these pages are contained in severe cases of textual elements compounds. According to the results obtained in our experiments in various areas of products and e-commerce stores, we validate the hypothesis that the extraction based on only textual features is possible and e ective. / Nessa dissertação de mestrado propomos um novo método para extração em páginas Web ricas em dados que utiliza apenas o conteúdo textual destas páginas. Nosso método, chamado de FIEX (Format Independent Web Data Extraction), é baseado em técnicas de extração de informação por segmentação de texto, e consegue extrair dados de páginas Web nas quais métodos do estado-da-arte baseados em técnicas de alinhamento de dados não conseguem devido à inconsistência entre a estrutura lógica das páginas Web e a estrutura conceitual dos dados nelas representadas. O FIEX, diferentemente dos métodos previamente propostos na literatura, é capaz de extrair dados apenas utilizando o conteúdo textual de uma página Web em cenários desa adores como casos severos de elementos textuais compostos, nos quais diversos valores de interesse para extração estão representados por apenas um elemento HTML. Para realizar a extração dos dados de páginas Web, o FIEX, é baseado em técnicas de eliminação de ruídos por redundância de informação e um método de extração de informação por segmentação de texto conhecido na literatura como ONDUX (On-Demand Unsupervised Learning for Information Extraction). Em nossos experimentos, utilizamos várias coleções de páginas Web de diferentes domínios de produtos e de lojas de comércio eletr ônico com objetivo de extrair dados de descrições de produtos. A escolha desse tipo de página Web, deve-se à grande quantidade de dados destas páginas estarem contidos em casos severos de elementos textuais compostos. De acordo com os resultados obtidos em nossos experimentos em diferentes domínios de produtos e lojas de comércio eletrônico, validamos a hipótese de que a extração baseada em apenas características textuais é possível e e caz.