Background: The companies of Industry 4.0 need to invest in digitalising their organizations as software is growing into a decisive manufacturing determinant. Especially in the SaaS business and the transformation to Industry 4.0, there are many small companies that are driving the transformation while competing for market share. In this context, the SaaS providers need to develop an understanding of the success of their solution. While the Information Systems Success Model by DeLone and McLean has found some application in the context of SaaS solutions, there is no specific model for the SaaS industry. Furthermore, there is the underlying need to understand which antecedents cause or influence the success of an information system. Purpose: The purpose of this study is to develop an Information Systems Success Model for Software-as-a-Service companies and to understand the antecedents and their relationships to the success of SaaS solutions from the SaaS provider’s point of view. Method: This study followed an abductive approach due to the possibility to simultaneously review existing theory and examine the empirical findings in the analysis. Furthermore, an exploratory study was conducted utilizing both quantitative and qualitative methods. The quantitative data was gathered through a standardized online survey of the customers of a SaaS provider and then analysed using Structural Equation Modelling. The qualitative data was collected through semi-structured interviews with SaaS providers, SaaS customers, and researchers of related fields and then analysed using a hermeneutic data analysis approach. The results of both methods were then triangulated to create the adapted model. Conclusion: Three antecedents of information systems success in the SaaS context were identified as part of this study. The antecedents are Management Support, User Involvement, and Trust. These antecedents can be used as levers by the SaaS provider to steer the success of their solution. Furthermore, the antecedents are integrated in a comprehensive Information Systems Success Model to measure and understand the success of SaaS solutions from the SaaS provider’s point of view.

Os sistemas de informação para inteligência de negócio (conhecidos também como BI - Business Intelligence) têm o propósito de coletar, estruturar, preparar e disponibilizar informações referentes aos processos internos e ao ambiente externo das organizações. O uso dessas informações visa suportar o processo de tomada de decisão bem como administração e inovação dos próprios processos de negócio das organizações. Dessa forma, essa classe de sistemas de informações (BI) tem o potencial de melhorar o desempenho individual e organizacional, sendo uma fonte de vantagem competitiva para as organizações. A abordagem de sistemas para BI não pode ser considerada somente como uma sequência de projetos isolados para disponibilização de informações. A gestão das demandas de informações necessárias para o negócio requer um esforço permanente para manter a função de BI alinhada com as necessidades da organização, através de processos que garantam a disponibilidade, o uso de informações e análises compartilhadas com base nos mesmos conceitos, documentação e organização das informações, assim como o suporte e treinamento técnico e funcional nos sistemas existentes. Nesse contexto, surgiu a proposta dos centros de competências de informações para BI, como uma estrutura de suporte para todas as áreas de negócio, sendo o elemento de ligação entre a área de tecnologia da informação e as diversas áreas da empresa para a gestão corporativa das informações. Este trabalho se propôs a operacionalizar uma forma de classificar as estruturas de gestão de informações para BI que são encontradas nas organizações, verificando o efeito de cada tipo de estrutura na qualidade percebida das informações disponibilizadas para as áreas de negócio, bem como o impacto para atividades dos indivíduos nas organizações que utilizam sistemas de BI. Foi realizada uma pesquisa quantitativa em três organizações, cada uma compondo uma amostra de cada tipo de estrutura de gestão de informações. Com a aplicação da técnica estatística de PLS, foi possível obter os efeitos entre as variáveis QI (Qualidade da informação), QGI (Qualidade da Gestão da Informação) e II (Impacto individual), moderados pelo tipo de estrutura de gestão de informações. Apesar de terem sido obtidas diferenças estatisticamente significantes entre as amostras, isto é, que as influências de QGI e QI em II variam estatisticamente de acordo com o tipo de estrutura de gestão de informações, foram pequenas as diferenças absolutas dos efeitos entre as estruturas adotadas em cada organização. Porém, os resultados obtidos nesta pesquisa de caráter exploratório sugerem a necessidade de estudos em uma maior quantidade de organizações, com vários casos para cada tipo de estrutura, a fim de identificar se existe consistência do efeito da variável moderadora nas variáveis analisadas entre diferentes tipos de organizações. / Information systems for business intelligence are designed to collect, organize, prepare and make available information related to internal processes and external environment of organizations. The use of this information is intended to support the process of decision making, business management and innovation of the processes of organizations. Thus, this class of information systems (BI) has the potential to improve individual and organizational performance, being a source of competitive advantage for organizations. The approach to deploy and sustain this class of information of system (BI) cannot be only a sequence of individual projects to make available information required during the scope phase of the project. Demand and delivery management of information necessary for the business requires an ongoing effort to maintain the function of BI aligned with the needs of the organization, through processes that ensure the information availability, use of shared information, information analysis across the organization based on the same concepts, documentation and organization of information, as well as support and training in technical and functional aspects of the systems. In this context, it has emerged the competence centers of information for BI, as a support organization for all areas of business, being the liaison between the area of information technology and the various areas of the company for corporate management of Information. This study proposes to operationalize a framework to classify the structures of information management for BI that are normally found in organizations and check the effect of each type of structure in the perceived quality of the information provided to the business areas as well the impact on individual activities for organizations that use BI systems. It was performed a quantitative study in three organizations, each one composing a sample of each type of management structure information. With the application of the statistical technique of PLS, it was possible to obtain the effects between variables QI (Quality of Information), QGI (Quality of Information Management) and II (Individual impact), moderated by the variable called \"type of information management structure\". Despite having been obtained statistically significant differences between the samples, in other words, that the influence of QGI and QI on II statistically vary according to the type of information management structure, the absolute differences of the effects were small between the respective structures adopted in each organization. However, the results obtained in this exploratory study suggest the need to research a larger number of organizations with multiple cases for each type of structure, in order to identify whether there is consistency in the effect of the moderating variable on the other variables among different types of organizations.

Information systems (IS) projects are complex and costly, but only a 3rd of IS projects are successful; the Standish Group reported that 32% of IS projects were successful in 2012. Although investments in research have led to improvements in practice, there is a general perception that management failures are responsible for the low rate of IS project success. The effects of initiating factors on project outcome had not been sufficiently explored; few IS researchers have explored the initiation phase. The purpose of this grounded theory study was to explore project initiation factors, including relational, as well as decision-making aspects, and how they might be addressed to enhance the possibility of success. The research questions were oriented at identifying key initiation factors, how they might be managed to promote project success, and how decision-making factors at initiation might facilitate project success. A conceptual framework consisting of chaos theory and Ashby's law of requisite variety was used. Purposive and snowballing sampling techniques were used, and 24 IS managers and project managers were interviewed. A 3-stage data analysis approach was used and included open coding, focused coding, and theoretical coding. Key themes identified included project governance and management, as well as stakeholder engagement. The emergent theory of IS project initiation indicated that the factors represented by the themes must be identified during initiation but implemented throughout the project lifecycle to ensure project success. Positive social change may be realized as IS managers, and project managers apply the findings and recommendations to achieve project success and avoid costly failures thus benefiting both companies and customers.

Industrial-organizational psychologist Stephen S.W. Gilliland developed a model for studying job-seeker fairness perceptions in 1993 based on existing research in organizational justice. The model includes several rules which will result in job-seeker perceptions of fairness if satisfied and job-seeker perceptions of unfairness if violated. Given the prominence of this model in the literature as well as changes which have occurred in personnel selection (such as human resource information systems, or HRIS, and e-recruitment), scholars have called for a technological re-envisioning of the original model, especially the explanations/descriptions ascribed to each rule. The present study seeks to understand how HRIS e-recruitment technology impacts job-seeker fairness perceptions and in so doing update the Gilliland (1993) model using a qualitative methodology and website success measures from information systems success theory. It contributes to the literature on applicant fairness perceptions by accounting for technological change, and contributes to the field of Public Administration by studying a governmental e-recruitment portal thereby accounting for the particularities of public-sector HRM which is underrepresented in the organizational justice literature. Over the course of one (1) year, twelve (12) job-seekers participated in a series of focus group interviews where they reflected on their experiences applying for jobs in the Canadian federal civil service using the government’s e-recruitment portal. Participants completed profiles, sent applications, communicated with government personnel, and wrote internet tests, among other job-search activities, and reported on their experiences from the perspective of fairness. Results confirm the validity of all original procedural justice rules and offer insight into their application in a recruitment environment where applicants invest considerable time interacting with computerized systems. Two additional rules are also put forth including the ease with which candidates can deceive tests and privacy/trustworthiness using technology. The findings are limited insofar as data gathering took place during a time of reduced hiring activity by the employer and because participation was limited to one (1) specific geographic location.

Os sistemas de informação para inteligência de negócio (conhecidos também como BI - Business Intelligence) têm o propósito de coletar, estruturar, preparar e disponibilizar informações referentes aos processos internos e ao ambiente externo das organizações. O uso dessas informações visa suportar o processo de tomada de decisão bem como administração e inovação dos próprios processos de negócio das organizações. Dessa forma, essa classe de sistemas de informações (BI) tem o potencial de melhorar o desempenho individual e organizacional, sendo uma fonte de vantagem competitiva para as organizações. A abordagem de sistemas para BI não pode ser considerada somente como uma sequência de projetos isolados para disponibilização de informações. A gestão das demandas de informações necessárias para o negócio requer um esforço permanente para manter a função de BI alinhada com as necessidades da organização, através de processos que garantam a disponibilidade, o uso de informações e análises compartilhadas com base nos mesmos conceitos, documentação e organização das informações, assim como o suporte e treinamento técnico e funcional nos sistemas existentes. Nesse contexto, surgiu a proposta dos centros de competências de informações para BI, como uma estrutura de suporte para todas as áreas de negócio, sendo o elemento de ligação entre a área de tecnologia da informação e as diversas áreas da empresa para a gestão corporativa das informações. Este trabalho se propôs a operacionalizar uma forma de classificar as estruturas de gestão de informações para BI que são encontradas nas organizações, verificando o efeito de cada tipo de estrutura na qualidade percebida das informações disponibilizadas para as áreas de negócio, bem como o impacto para atividades dos indivíduos nas organizações que utilizam sistemas de BI. Foi realizada uma pesquisa quantitativa em três organizações, cada uma compondo uma amostra de cada tipo de estrutura de gestão de informações. Com a aplicação da técnica estatística de PLS, foi possível obter os efeitos entre as variáveis QI (Qualidade da informação), QGI (Qualidade da Gestão da Informação) e II (Impacto individual), moderados pelo tipo de estrutura de gestão de informações. Apesar de terem sido obtidas diferenças estatisticamente significantes entre as amostras, isto é, que as influências de QGI e QI em II variam estatisticamente de acordo com o tipo de estrutura de gestão de informações, foram pequenas as diferenças absolutas dos efeitos entre as estruturas adotadas em cada organização. Porém, os resultados obtidos nesta pesquisa de caráter exploratório sugerem a necessidade de estudos em uma maior quantidade de organizações, com vários casos para cada tipo de estrutura, a fim de identificar se existe consistência do efeito da variável moderadora nas variáveis analisadas entre diferentes tipos de organizações. / Information systems for business intelligence are designed to collect, organize, prepare and make available information related to internal processes and external environment of organizations. The use of this information is intended to support the process of decision making, business management and innovation of the processes of organizations. Thus, this class of information systems (BI) has the potential to improve individual and organizational performance, being a source of competitive advantage for organizations. The approach to deploy and sustain this class of information of system (BI) cannot be only a sequence of individual projects to make available information required during the scope phase of the project. Demand and delivery management of information necessary for the business requires an ongoing effort to maintain the function of BI aligned with the needs of the organization, through processes that ensure the information availability, use of shared information, information analysis across the organization based on the same concepts, documentation and organization of information, as well as support and training in technical and functional aspects of the systems. In this context, it has emerged the competence centers of information for BI, as a support organization for all areas of business, being the liaison between the area of information technology and the various areas of the company for corporate management of Information. This study proposes to operationalize a framework to classify the structures of information management for BI that are normally found in organizations and check the effect of each type of structure in the perceived quality of the information provided to the business areas as well the impact on individual activities for organizations that use BI systems. It was performed a quantitative study in three organizations, each one composing a sample of each type of management structure information. With the application of the statistical technique of PLS, it was possible to obtain the effects between variables QI (Quality of Information), QGI (Quality of Information Management) and II (Individual impact), moderated by the variable called \"type of information management structure\". Despite having been obtained statistically significant differences between the samples, in other words, that the influence of QGI and QI on II statistically vary according to the type of information management structure, the absolute differences of the effects were small between the respective structures adopted in each organization. However, the results obtained in this exploratory study suggest the need to research a larger number of organizations with multiple cases for each type of structure, in order to identify whether there is consistency in the effect of the moderating variable on the other variables among different types of organizations.