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In today’s world, a lot of various kinds of raw materials are shipped from one place to another as per the requirement of industries. This shipping process involved many multiple levels with multiple personalities or authorities. The intermediates may be influenced by some illegal external factors and there may be some theft or modification in the raw material which is in the shipping process. This generates a significant loss if the material is of high cost. Presently, the advancements in information technology precede a method to restrict this loss and it is blockchain. Blockchain technology is an essential feature in enabling a comprehensive view of events back to origination. The shipping chain of raw materials that provides integrity and tamper resistance for raw materials in the shipping process is proposed in the manuscript. we have also provided proof of concept (PoC) in Hyperledger Composer with performance evaluation. info:eu-repo/semantics/publishedVersion

The purpose of this paper is to compare the strategies of companies with data science practices and methodologies and the data specificities/variables that can influence the definition of a data science strategy in pharma companies. The current paper is an empirical study, and the research approach consists of verifying against a set of statistical tests the differences between companies with a data science strategy and companies without a data science strategy. We have designed a specific questionnaire and applied it to a sample of 280 pharma companies. The main findings are based on the analysis of these variables: overwhelming volume, managing unstructured data, data quality, availability of data, access rights to data, data ownership issues, cost of data, lack of pre-processing facilities, lack of technology, shortage of talent/skills, privacy concerns and regulatory risks, security, and difficulties of data portability regarding companies with a data science strategy and companies without a data science strategy. The paper offers an in-depth comparative analysis between companies with or without a data science strategy, and the key limitation is regarding the literature review as a consequence of the novelty of the theme; there is a lack of scientific studies regarding this specific aspect of data science. In terms of the practical business implications, an organization with a data science strategy will have better direction and management practices as the decision-making process is based on accurate and valuable data, but it needs data scientists skills to fulfil those goals. info:eu-repo/semantics/acceptedVersion

With the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social media tools in disaster information emergency management. Weibo is the most widely used Chinese social media tool. To effectively mine and apply the emergency function of disaster situation microblogs, a disaster situation information discovery and collection system capable of online incremental identification and collection are constructed for massive and disordered disaster microblog text streams. First, based on the deep learning- trained word vector model and a large-scale corpus, an unsupervised short-text feature representation method of disaster situation Weibo information is developed. According to the experimental results of the feature combination test and the training set scale test, the SVM algorithm was selected for disaster microblog information classification, which realized effective identification of disaster situation micro-bloggings. Then, the temporal information similarity and geographic information similarity are used to improve the single text similarity algorithm, and a Chinese disaster event online real-time detection model is constructed. Furthermore, the disaster-affected areas can be achieved in real-time based on the detection results. By crawling and classifying the micro-bloggings from the disaster-affected areas, it is possible to realize the incremental identification and collection of online disaster situation Weibo information. Finally, the empirical analysis of disaster events such as the “Leshan Earthquake” shows that the real- time intelligent identification and collection system for disaster situation Weibo micro-bloggings developed in this paper can obtain large-scale and useful data for disaster emergency management, which proving that this system is effective and efficient.

The applications related to ultra-low power wearables like internet of things, robotics, intrusion detection, and image security have become a major computing paradigm and the latest disruptive technology after artificial intelligence. Ability of ultra-low power wearables to connect with other systems and applications from low to high level has prompted unprecedented array of applications in all fields of human activity from science, engineering, health, leisure and everyday life, etc. The technological growth in ultra-low power wearables is going hand-by-hand with enormous research efforts by an ever increasing community in a fascinating multidisciplinary field. The motivation of this special issue is to offer an essential guide to the readers on the applications: internet of things security, wireless sensor network, image processing, intrusion detection, antenna, optimization, and cryptography. The accepted manuscripts are used as a reference text for graduate and undergraduate studies. Hence, the manuscripts are written in plain and easy to follow language and explain every main concept the first time it appears, helping readers with no prior background in the field. It is a “must-read” guide to the subject matter. This special issue intends to provide a platform for researchers to share innovative work in many applications like internet of things security, wireless sensor network, image processing, intrusion detection, antenna, optimization, and cryptography. After a double-blinded peer-review procedure, 14 papers have been accepted and included in this special issue, which contains different methods to solve different kinds of complex problems.

This Special Issue is dedicated to current issues in Decision-making and Negotiation in Innovation & Research in Information Science. Despite all the research around Decision-making and Negotiation the main theoretical and practical importance of this issue is the focus on studies oriented to innovation & research (I&R) in information science. The purpose is to analyse the decision-making processes for practical problem-solving and to understand the ways information systems can be a trigger in the process. To achieve this objective several articles will present models, tools and frameworks to help improving the decision-making and negotiation processes, and the research findings support the conclusion that information systems can help to achieve better decisions and facilitate the negotiation processes.

Higher education institutions (HEIs) are complex and dynamic organizations in terms of information management, forcing their information systems to respond to enormous challenges and threats. In order to evaluate the HEIs’ information systems, we propose the development of a maturity model capable of supporting the role of HEI’s managers, as well as accreditation agencies, in the assessment of the maturity of these systems, thus, promoting continuous improvement. In this paper, we present and discuss our proposal for an architecture of the maturity model being developed. This one is based on a two-dimensional architecture composed of vertical and horizontal dimensions. We selected a multi-case study approach, based on five Portuguese HEIs, and reviewed the literature to identify the dimensions. This case study was supported by interviews with experts from the selected HEI. The results of this research work were both encouraging and promising amongst the interviewed experts, revealing a high level of acceptance of the general model architecture, as well as positive expectations about its usefulness in the future. The development of our maturity model is carried out by following a formal methodology specially designed to support the construction of this type of model.

In the last five decades, maturity models have been introduced as reference frameworks for Information System (IS) management in organizations within different industries. In the healthcare domain, maturity models have also been used to address a wide variety of challenges and the high demand for hospital IS (HIS) implementations. The increasing volume of data, is exceeded the ability of health organizations to process it for improving clinical and financial efficiencies and quality of care. It is believed that careful and attentive use of Data Analytics in healthcare can transform data into knowledge that can improve patient outcomes and operational efficiency. A maturity model in this conjuncture, is a way of identifying strengths and weaknesses of the HIS maturity and thus, find a way for improvement and evolution. This paper presents a proposal to measure Hospitals Information Systems maturity with regard to Data Analytics. The outcome of this paper is a maturity model, which includes six stages of HIS growth and maturity progression.

Assuring the quality control of publications in the scientific literature is one of the main challenges of the peer review process. Consequently, there has been an increasing demand for computing solutions that will help to maintain the quality of this process. Recently, the use of Artificial Intelligence techniques has been highlighted, applied in the detection of plagiarism, bias, among other functions. The assessment of the reviewer’s review has also been considered as important in the process, but, little is known about it, for instance, which techniques have been applied in this assessment or which criteria have been assessed. Therefore, this systematic literature review aims to find evidence regarding the computational approaches that have been used to evaluate reviewers' reports. In order to achieve this, five online databases were selected, from which 72 articles were identified that met the inclusion criteria of this review, all of which have been published since 2000. The result returned 10 relevant studies meeting the evaluation requirements of scientific article reviews. The review revealed that mechanisms to rank review reports according to a score, as well as the word analysis, are the most common tools, and that there is no consensus on quality criteria. The systematic literature review has shown that reviewers’ report assessment is a valid tool for maintaining quality throughout the process. However, it still needs to be further developed if it is to be used as a resource which surpass a single conference or journal, making the peer review process more rigorous and less based on random choice.

In the educational environment field of teaching and learning for the SQL language, there have been recent approaches that use heuristic methods to categorize and discover information about student errors. The categorization of student source code errors by the level of complexity of the problem was one of the limitations found in these approaches. Owing to this limitation, the conclusions drawn from these studies are superficial and do not explain the real reasons that led the students to make their mistakes. As an alternative, we propose a new methodology that uses cluster-based decision trees and the fundamentals of the programming language to discover the most relevant patterns of knowledge about student behaviour. Through an innovative architecture for classifying errors, the methodology allows us to explain: (a) what are the most frequently committed errors, (b) when these errors usually occur and (c) the reasons that led to the error. The methodology was applied in a case study with more than 105,200 SQL queries, which, in addition to explaining the hypotheses about what leads students to make mistakes, also gave the following results: (1) it proved the concept of reducing the breadth of analysis of the decision tree, (2) it showed that an error database could be used for the discovery of knowledge and (3) it resulted in the discovery of a set of 66 rules; 12 related to semantic errors and 54 to syntax errors. The rules identified the error, when the mistake was made and why the student made the mistake. The methodology uses an architecture based on the fundamentals of the programming language and can therefore be adapted for use in another context.

The article is devoted to the assessment of existing level of development of information and consulting system in agricultural and industrial complex. The relevance of covering methodological issues is due to the current level of development of information and consulting services in regions, the rapid and large-scale expansion of the Internet space, the established world experience in introducing innovations, and the need to implement state policy in the field of agriculture. The paper considers the works of Russian scientists and economists on improving the system of agricultural consulting. The positive world experience of spreading an effective system of innovative and consulting services of rural areas is studied. For discussion, the authors propose a methodology for choosing a model of an innovative service center in rural areas. The effectiveness of application of comprehensive information system with the involvement of educational organizations is justified. The experience of functioning of Center for Support of Rural Development on the basis of regional university is presented. The authors formulate proposals for improving the innovation and consulting infrastructure in the agricultural and industrial complex in order to increase the efficiency of providing information and consulting services, increase the level of knowledge of rural population, the personnel of agricultural producers, disseminate information about the achievements of scientific and technical community, innovative developments and methods of management, effective interaction of agricultural entities, authorities, scientific and educational organizations.

Supported by an environment that is increasingly immersed in digital transformation, universities are facing important organizational changes in both tangible and intangible structures. Digital transformation isn’t all about technology, there is a human side of the story. Leadership is seen as a key issue in any process of change. However, leaders of professional and knowledge-based institutions, like universities, face special demands. The present article aims to synthesize what has been investigated about leadership in the context of University 4.0. A systematic approach was adopted in conducting the literature review. The main body of the article focuses on illustrating five thematic clusters grounded in the literature and identifying co-citation network of each cluster using bibliometrics. Results demonstrate that this is an emerging theme. This paper is the first attempt to systematically review all research that so far has been made available in the broad field of leadership in University 4.0.

Big Data technology is one of the most promising organizational processes within the Healthcare and Pharmaceutical industry and crucial for any company that wants to preserve the competitive advantage in the market, where most of the organizational structures are already struggling with the right skills and knowledge to fully support existing business needs for storing and processing and even analyzing information. This paper aims to examine the extent to which new Big Data technology and data-related processes are developing different professionals skills and competencies within the Healthcare and Pharmaceutical industries, and creating sustainable development in addressing critical organizational challenges in recruiting, retaining, and discover professional skills that can fully support the advances and exponential growth of Big Data technology benefits. This research paper also highlights the significant aspects of Big Data in professional technical and process oriented skills development, and the influence it has on organizational business processes including how various internal functions will need to adapt to new circumstances with renewed competency and skills development programs for departments that are strongly connected to the business and analytical needs. We conducted a focus group with twenty-five industry based professionals’ ranges from analysts to executive directors to better assess the necessary knowledge to answer the proposed research questions: (1) which professional skills can big data influence in employee development and (2) how can organizations adapt their employee skills to big data. Regarding the key research limitations/implications most of the article and research was built on the foundation of the literature review and the performed focus group. The conceptual recommendations and observations presented provide solid empirical evidence but should be subjected to more comprehensive, large-scale empirical testing and validation. It’s recommended for future research a more extensive sample of companies, organizations, and interviewees. Studying a broader set of similar research questions in more homogeneous organizations could provide deeper insights into the process, governance, and stakeholder dimensions of Big Data within specific contexts. Therefore this study contributes to explore in-depth and systematically to what extent Big Data technology and processes are currently influencing the healthcare and pharmaceuticals industries where to the best of the authors’ knowledge, it is the first focus group dealing with the presented research questions.

In the last five decades, maturity models have been introduced as guides and reference frameworks for information system (IS) management in organizations within different industries and sectors. In the healthcare domain, maturity models have also been used to address a wide variety of challenges, complexities and the high demand for hospital IS (HIS) implementations. The present paper describes a research project focused on the development of a comprehensive maturity model applied in the HIS context. The outcome of this research is the HIS maturity model (hereafter referred to as HISMM), which includes six stages of HIS growth and maturity progression. The HISMM has the peculiarity of congregating a set of key maturity-influencing factors and respective characteristics, enabling not only the assessment of the global maturity of a HIS, but also the individual maturity of its different dimensions.

“Cyber-attacks can be more dangerous than guns and tanks”. This statement was made by Junker in his speech in the EU “State of the Union” in 2017 and reflects the extreme importance of this phenomenon. The increasing variety of devices that can access to Internet has contributed to the overall growth of internet users, in all kinds of places and circumstances. These devices are now part of our lives and we use it for everything. As the number of devices and tasks that we do with it are growing, more prone we are to cyber-attacks. As well, as the number of user’s victim of these attacks are increasing, the general concerns about cybercrime are growing too. The growing list of cybercrimes includes crimes that have been made possible by computers, such as network intrusions and the dissemination of computer viruses, as well as computer-based variations of existing crimes, such as identity theft and terrorism which have become as major problem to people and nations. In this context, the European Union is leading the effort to regulate the defence against cyber-threats in both normative/legal and strategic levels. This reality is also very present in Portugal, where there is a sense of lack of control and capacity to combat this kind of threats. In this article, we present the European Strategy and Legislation for Cybersecurity and how this strategy applies and involves Portugal.

With the advent of the era of big data, massive data make the informationization work of academic libraries severely challenging in all aspects. The application of data mining technology to the various services of academic libraries to cope with this challenge has gradually become the mainstream trend. In order to better detect the overall trends and research hot spots of data mining in Chinese academic libraries, 329 related studies were extracted from CNKI (China National Knowledge Infrastructure) and analyzed by using bibliometrics and keyword network analyses. Bibliometrics was used to analyze the distribution of the overall trends, authors, institutions, research levels, and keywords in the related field. Cluster analysis was applied to the keyword co-occurrence network to show hot issues in the application research of data mining in Chinese academic libraries. Results indicate that findings in this area generally show an upward trend, but few high-yielding authors are found, the volume of journals is low, research institutions are scattered, and the rate of funding support is not high. At the method level, association rules and cluster analysis are hot data mining technologies in Chinese academic library research. At the application level, the fields related to personalized services and big data continue to be hot research areas.

This paper presents a research on the effectiveness of digital learning in organisations and how it can be measured. This research aims to bridge the gap between scientific and practice-oriented research about digital learning. The focus will be on learning analytics and measuring its impacts on organisations with the goal to identify the potential of digital learning for organisations. This research is based on a systematic literature review and a survey analysis to answer the following research questions: What are the contexts in which digital learning can take place? What are the main metrics which allows measuring the efficiency of digital learning in organisational contexts? Is there a positive influence of the digital learning contexts supported by organisations, on skills development and impacts on performance analytics that measure the impacts in organisations? And what is the digital learning analytics that measures the impacts on organisations? What is the digital learning analytics that measures the impacts on organisations? The results showed that digital learning analytics can enhance the efficacy of the learning process impact in organisations and that contexts for learning supported on mobile technologies, tablet and smartphone applications become more and more popular among the employees. Additionally, the results helped to create a model of learning analytics and identify impacts of the learning process.

Analizamos la literatura académica internacional centrada en los teléfonos móviles y las terapias psicosociales. Identificamos los artículos publicados entre 2000 y 2015 en las bases de datos disponibles en Internet; y ponemos en evidencia las escasas investigaciones con personas vulnerables. La literatura especializada en terapias psicosociales muestra interés en las utilidades de los teléfonos móviles en pacientes en general, con mayor producción desde la psicología y en menor medida desde el trabajo social. Destacan las investigaciones desarrolladas en los Estados Unidos y su escasa existencia en España, donde se discuten las competencias del trabajador social en este campo. Identificamos oportunidades y limitaciones en cuanto a la privacidad de los datos, al acceso a los teléfonos móviles y a su uso; para llegar a poblaciones aisladas o de escasos recursos o para facilitar el acceso a los servicios sociales y de salud. Concluimos con posibles orientaciones, hipótesis y objetivos en el diseño de nuevas investigaciones. We analyse international academic literature focused on mobile phones and psychosocial therapies. We identify articles published between 2000 and 2015 and available on Internet databases; and we highlight the scarce number of investigations focusing on vulnerable people. Literature specializing in psychosocial therapies address the usefulness of mobile phones in patients in general, with greater production from psychology and to a lesser extent from social work. We highlight the research developed in the USA and its residualness in Spain, where debates focus on the competences of the social worker in this field. We identify opportunities and limitations in terms of data privacy, access to and use of mobile phones; to reach isolated or poor populations or to facilitate access to social and health services. We conclude with possible orientations, hypotheses and goals for prospective investigation works SI

Effective knowledge management practices in organizations are focused on knowledge creation and knowledge transfer activities. Thus, intelligence and competencies matters at the organizational workplace. For most knowledge intensive organizations is fundamental the continuous availability and development of domain expertise. This paper describes an ongoing research project to develop an organizational knowledge architecture that is being specified and developed to support collaboration tasks as well as design and model predictive data analysis and insights for organizational development. The primary goal of this research is to create a suitable architecture for use, initially, in intranet (corporate portal) collaborative procedures, but also scalable for later use in more generic forms of ontology-driven knowledge management systems. The designed architecture and functionalities aim to create coherent web data layers for intranet learning and predictive analysis, defining the vocabulary and semantics for knowledge sharing and reuse projects. Regarding intellectual capital definition, this research argues that effective knowledge management are based on the dynamic nature of the organizational knowledge, and predictive data analysis and insights identification can transform and add value to an organization. This paper presents a knowledge management and engineering perspective (ontology based) for the application of predictive analysis and insights at the organizational (corporate) workplace towards the development of the organizational learning network.

This article presents the first phase of a research project whose purpose is to introduce a new form of collaboration and communication between the school and the family through an Electronic Booklet (EB). The EB was developed due to the increasing necessity of collaboration between the school and the family, promoting the teaching-learning process and educational success, supported by information and communication technologies. These conclusions and justifications were derived from a survey based in a questionnaire applied to guardians and teachers of several private and public Portuguese schools of the primary and secondary education level. Both groups – guardians and teachers stressed the importance of communication between school and family and expressed interest in the EB as a communication tool. The analysis of the survey results made possible the construction of an Electronics Booklet prototype.

Maturity models facilitate organizational management, including information systems management, with hospital organizations no exception. This article puts forth a study carried out with a group of experts in the field of hospital information systems management with a view to identifying the main influencing factors to be included in an encompassing maturity model for hospital information systems management. This study is based on the results of a literature review, which identified maturity models in the health field and relevant influencing factors. The development of this model is justified to the extent that the available maturity models for the hospital information systems management field reveal multiple limitations, including lack of detail, absence of tools to determine their maturity and lack of characterization for stages of maturity structured by different influencing factors.

© The Author(s) 2018. Mobile phones can produce detailed and personalized data to help diagnose, treat, prevent or rehabilitate women who are victims of gender violence. We sent automatic text messages, based on cognitive-behavioural therapy, to female victims of gender violence to assess the feasibility of the medium for mental health intervention. During the 28-day intervention period, each woman received four automatic text messages every day on a pre-established schedule. We evaluated symptoms of depression using the Personal Health Questionnaire-9. The Personal Health Questionnaire-9 decreased from an average of 14.8 at the beginning of the intervention, to 6.1 at the end of the text messaging period. All of the women reported that they liked receiving the messages, they found them useful and they felt that the messages had improved their health. Text messages are acceptable to women users who are recipients of public health and social services. Future research should focus more on the evaluation of the results and on how the specific content and aspects of text messaging improve health outcomes.

The problem discussed in this paper is the paradox associated with hundreds of contributions of the scientific community over three decades, mainly leveraged by the Strategic Alignment Model (SAM) and its perspectives, but whose benefits arising from its applicability to the real world are scarce. The context of public sector organizations, which does not fit into any of the four perspectives presented by Henderson and Venkatraman (1993), led to the intertwining of the theme with Data Science. The hypothesis formulation involves interconnecting convergent concepts, namely through the adoption of a replicable framework in any world-wide public services, to potentiate the change of perspective, allowing to achieve the desired strategic alignment (IT-Business). It is hoped that the suggestions and recommendations can contribute to leverage significant changes in the Public Sector context in order to optimize the services provided, anticipating the citizen’s needs.

With the evolution and popularization of mobile communication sys-tems, especially for access to data services, it becomes increasingly important to have a closer look at security systems. From analog systems to the fourth gener-ation, many changes and evolutions occurred. This makes possible to question whether mobile networks have sufficiently secure systems, and what vulnerabil-ities we should be aware of. Due to the widespread risk of attacks on mobile communications, telecommunication companies are increasingly emphasizing telecommunication security technologies specifically in fourth generation (4G) technology, in order to ensure the main security functions for to provide an effi-cient service to its customers. info:eu-repo/semantics/publishedVersion

Various experimental studies on psychosocial therapy have been carried out through text messages with groups of people suffering from depression, anxiety, alcoholism, addictions, etc., but without distinguishing between men and women or highly vulnerable groups such as immigrants. We present an exploratory study of a mobile communication system which intends to improve the mental, physical and social health of a group of vulnerable immigrant women in Spain (n = 71), distinguishing between an intervention group and a non-equivalent control group. We sent automatic text messages (SMS) to the mobile phones of an intervention group formed by immigrant women who used the social services (n = 44). During a 26-day intervention period, the women received 4 daily automatic text messages on their phones, at a predetermined time. We measured mood and depression symptoms at the beginning and end of the intervention, and analysed the qualitative data to determine the acceptance level of a remote message program. The mood and depression symptoms were measured with the personal health questionnaire-9 (PHQ-9) and were significantly better in the intervention group; they evolved from an initial 9.4 (DS = 6.4, range 1-25) to a 5.0 score at the end of the message period (DS = 4.8); with a significant difference (t (44) = 2.01, p = 7.80). Most women stated that the messages had improved their mood (86.3%), which made them feel more connected to their social environment (65.9%) and that they would like to continue receiving more messages (86.6%).

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean). This research was supported by the Cluster Research Projects Activity code # R16086 and R18027, Zayed University, Abu Dhabi, United Arab Emirates.

The primary goal of this paper is to contribute to the discussion of an effective digital transformation of organizations based on the latest trends of skills. It also intends to analyze the perceptions of individuals regarding the challenges faced by organizations and opportunities for new disruptive business. A literature review about the digital learning contexts and the identification of skills needed for organizations digital transformation was made. Moreover, it was also launched an online survey to identify the importance of skills for an effective digital transformation. As primary results, the main skills identified were artificial intelligence, nanotechnology, robotization, internet of things, augmented reality, digitalization; and the main digital learning contexts were mobile technologies, tablets, and smartphone applications — which are becoming more and more popular among the employees. This study will help organizations to rethink their strategies according to skills development to respond to the challenges of digital transformation. AISTI (Associacao Iberica de Sistemas e Tecnologias de Informacao/lberian Association for Information Systems and Technologies, Portugal)

This article analyses the concept of skills and also investigates the skills needed to create and manage disruptive digital business which is emerging from the IT evolution. The primary purpose is to identify skills which need to be developed to manage a disruptive digital business. The technologies, disruptive business and the skills needed by managers were identified through content analysis of semi-structured interviews with seven IT specialists. To analyze the development of the level of skills needed was conducted an online survey with managers and the final output of the research is a proposal of a model of skills' development for managers of the disruptive business. Ultimately, the result of this research are the lessons uncovered and the proposal made for a model of skills development for disruptive business managers, which identifies three types/categories of skills needing development - innovation, leadership, and management. FCT Foundation for Science and Technology (Portugal)Portuguese Foundation for Science and Technology [UID/SOC/04020/2013]

Game-based learning (GBL) as a universal approach to developing leadership skills have been winning attention from researchers and practitioners. There are numerous studies which support the positive effects of games on learning and knowledge development; however, more research is needed regarding how games may influence development of leadership skills. This paper examines recent literature regarding game-based learning influence in leadership skills development and if new leadership styles can emerge during a collaborative gaming process. The research questions were: 1) what were the leadership skills developed, during a GBL course? Moreover, 2) what kind of leadership styles emerge in the gaming context? The methodological approach was quantitative and also qualitative, privileging the interpretative approach and the primary technique used was content analysis from the forums of discussion of 8 GBL courses with 15 participants in each course summing a total of 120 individuals and also factor analysis based on data collected by a questionnaire about the leadership skills developed, and which conducted to the identification of the leadership styles. The findings suggest that a game-based learning approach is an effective approach to leadership skills development and the primary skills developed were: motivation, facilitation, coaching, mindset changing, and communication. The significant originality of the research was the analogy process between the games situations and the organisational life resulting on the creation of a leadership typology.