Information Systems

We study the relationship between Bitcoin trading volume, volatility, and returns using financial data for the period July 2010–November 2017. When we compare the raw annualized volatility of the Bitcoin exchange rate against common currencies, we observe that Bitcoin’s is higher. However, when the volume of Bitcoin transactions is considered, the volatility of the Bitcoin stabilizes significantly. Then we divide our sample into four distinct time periods, defined by three important events, namely, the loss of public confidence in the banking system in 2013, the MtGox Bitcoin Exchange hack in early 2014, and the introduction of the Bitcoin legislation in Japan in April 2017. Using asymmetric EGARCH models with the lag of the natural logarithm of the volume of the Bitcoin both as a regressor in the mean equation as well as in the specification of the conditional variance as multiplicative heteroskedasticity we show that volume and volatility are related after 2013, and volume and returns are related before the MtGox hack, positively and significantly. Further, during the euphoric period between the beginning of 2013 and up to the MtGox hack an unexpected rise in Bitcoin returns increases Bitcoin volatility more than an unexpected, equally sized decrease (asymmetry).

Blockchain provides the possibility to design new types of applications and systems that allow their users to store data in a secure and transparent way. In this paper, we design a fully verifiable online electronic voting protocol using a blockchain. Our e-voting protocol, called VYV for Verify-Your-Vote, involves cryptographic primitives based on Elliptic-Curve Cryptography (ECC), pairings and Identity Based Encryption (IBE). It ensures the following privacy and security properties: only eligible voter can vote, authentication of the voter, vote privacy, receipt-freeness, fairness, individual and universal verifiability. Furthermore, we formally prove the security of our protocol, using ProVerif tool.

During the last decade, Blockchain technology has attracted a lot of attention as it has the potential to disrupt the existing ecosystem and transform the way we do business. In this paper we investigate the energy supply chain and we examine the impact of the development of a blockchain solution in the area of solar energy. Our findings illustrate that blockchain technology can disrupt many areas of this sector including disruptions in the product, process, position and paradigm.

If blockchain technologies are emerging as important game changers in the supply chain, this is largely attributed to their high operational and strategic business value. While this high potential is acknowledged by the practitioner’s literature, very few empirical studies have been conducted on the factors explaining the adoption, use and continuance of blockchain-enabled supply chain applications. To fill this knowledge gap, this study extended the expectation-confirmation model (ECM) by integrating the supply chain stakeholders trust to analyze to the continuance intention in blockchain-enabled supply chain applications. The proposed model was tested and supported by the data collected among 344 supply chain professionals in India. The paper ends up with the formulation of important implications for practice and research.

While wildfires continue to ravage our world, big data analysis aspires to provide solutions to complex problems such as the prevention and management of natural disasters. In this study, we illustrate a state-of-the-art approach towards an enhancement of UAV (Unmanned Aerial Vehicle) surveillance for wildfire prevention and management through big data analysis. Its novelty lies in the instant delivery of images taken from UAVs and the (near) real-time big-data oriented image analysis. Instead of relying on stand-alone computers and time-consuming post-processing of the images, a big data cluster is used and a MapReduce algorithm is applied to identify images from wildfire burning areas. Experiments identified a significant gain regarding the time needed to analyze the data, while the execution time of the image analysis is not affected by the size of the pictures gathered by the UAVs. The integration of UAVs, Big Data components and image analysis provides the means for wildfire prevention and management authorities to follow the proposed methodology to organize their wildfire management plan in a reliable and timely manner. The proposed methodology highlights the role of Geospatial Big Data and is expected to contribute towards a more state-of-the-art knowledge transfer between wildfire confrontation operation centers and firefighting units in the field.

Apache Hadoop is a popular technology that proved itself as an effective and powerful framework for Big Data analytics. It broke from many of its predecessors in the “computing at scale” space by being designed to run in a distributed fashion across large amounts of commodity hardware instead of a few expensive computers. Many organizations have come to rely on Hadoop for dealing with the ever-increasing quantities of Big Data that they gather. “Harnessing cloud scalability to Hadoop clusters” means running Hadoop clusters on resources offered by a cloud provider on demand.

This article discusses the results of a multi-industry and multi-country survey carried out to understand the needs, requirements, and use of big data and analytics by public and private organizations in decision-making, business processes and emerging business models. In particular, these issues are analyzed in specific industries where big data exploitation may have not only an economic value but also and an impact on social value dimensions such as, e.g., public and personal safety. Furthermore, the survey aims at questioning the characteristics of big data ecosystems in different and specific domains, thus identifying existing or potential barriers to the development of new data-driven industrial sectors along the big data information value chain. Finally, the authors have identified three key challenges (big data efficiency, effectiveness, and accessibility) to classify the survey results that showed low utilization rate of the data collected, lack of right tools and capabilities, the low rate of digital transformation of the companies as the key concerns for the respondents.

From major companies and organizations to smaller ones around the world, databases are now one of the leading technologies for supporting most of organizational information assets. Their evolution allows us to store almost anything often without determining if it is in fact relevant to be saved or not. Hence, it is predictable that most information systems sooner or later will face some data management problems and consequently the performance problems that are unavoidably linked to. In this paper we tackle the data management problem with a proposal for a solution using machine-learning techniques, trying to understand in an intelligent manner the data in a database, according to its relevance for their users. Thus, identifying what is really important to who uses the system and being able to distinguish it from the rest of the data is a great way for creating new and efficient measures for managing data in an information system.

The paper presents a case study on the use of open big data in the Norwegian Parliament. A set of policy documents was examined to find motivation for publishing open data. The case study was based on an examination of the parliament website, combined with document studies and interviews. The paper concludes that third parties have used open data to create new applications that generate value for their users. Applying our findings to the open government benchmarking framework, we identify some national barriers and possible solutions to further promote the use and publication of open data.

Due to the complex and dynamic nature of Supply Chains (SCs), companies require solutions that integrate their Big Data sets and allow Big Data Analytics, ensuring that proactive measures are taken, instead of reactive ones. This paper proposes a proof-of-concept of a Big Data Warehouse (BDW) being developed at a company of the automotive industry and contributes to the state-of-the-art with the data requirements elicitation methodology that was applied, due to the lack of existing approaches in literature. The proposed methodology integrates goal-driven, user-driven and data-driven approaches in the data requirements elicitation of a BDW, complementing these different organizational views in the identification of the relevant data for supporting the decision-making process.

Addressing the increasing volumes of data requires specific technologies, sophisticated methods and tools. Recently, the Big data processing’ challenge gave a strong impulse to the development of new data technologies. Considering that organizations still use their traditional database applications, reconciliation of both cases will be a more effective way to manage data functions in the organizations. In this paper we propose a framework for processing Big data based on technologies provided by Oracle. We also discuss some performance aspects of the proposed framework.

Due to the extensive use of SQL, the number of SQL-on-Hadoop systems has significantly increased, transforming Big Data Analytics in a more accessible practice and allowing users to perform ad-hoc querying and interactive analysis. Therefore, it is of upmost importance to understand these querying tools and the specific contexts in which each one of them can be used to accomplish specific analytical needs. Due to the high number of available tools, this work performs a performance evaluation, using the well-known TPC-DS benchmark, of some of the most popular Big Data Analytical tools, analyzing in more detail the behavior of Drill, Hive, HAWQ, Impala, Presto, and Spark.

Distributed computational platforms, especially volunteer based ones, become popular over the past decades due to the cheap access to resources. The majority of these Volunteer Computing (VC) platforms are based on client-server architecture, therefore susceptible to server-side bottlenecks and delays in project completion due to lost Workload Units (WU). This paper presents a new model for a computing platform that offloads the tasks of WU creation from centralized servers to the network nodes and with the use of a remote checkpoint system, it can re-create lost WUs from failed or unavailable nodes. With these improvements, it can achieve better scaling and load balancing, and due to the checkpoints, only a limited amount of computation is lost due to node failure. Simulation results of the model’s behavior are also present and interpreted.

Dynamic workflow applications are increasingly used in many enterprises to satisfy the variable enterprise requirements. Cloud computing has gained a particular attention to run these applications. However, due to lack of formal description of the resource perspective, the behavior of Cloud resource allocation cannot be correctly managed. This paper fills this gap by proposing a formal model which verifies the correctness of dynamic workflow changes in a Cloud environment using the Event-B method. Our model considers properties related to control flow, data flow and resource perspectives. It aims to preserve the correctness of workflow properties at both design time and runtime.

Cloud computing technology offers promising business advantages for small and medium-sized enterprises. In Saudi Arabia, the adoption of cloud computing by SMEs has so far occurred relatively slowly. This study investigates the factors affecting the adoption of cloud computing by SMEs in Saudi Arabia. A sample of fourteen interviews conducted with IT experts provides a foundation for exploring new factors that affect this decision, as incorporated into a conceptual model developed for this study. This model draws on the Technology-Organisation-Environment framework but adjusted based on new contextual factors. Factors such as the duration of software implementation, software integration, and software customisation guided this study. Furthermore, experts were of the view that other factors such as culture and technology infrastructure also impacted the adoption of cloud computing among SMEs. This study bridges the gap in the literature on cloud computing adoption with new evidence from the unexplored context of Saudi Arabia.

Assessing and managing cloud risks can be a challenge, even for the cloud service providers (CSPs), due to the increased numbers of parties, devices and applications involved in cloud service delivery. The limited visibility of security controls down the supply chain, further exacerbates this risk assessment challenge. As such, we propose the Cloud Supply Chain Cyber Risk Assessment (CSCCRA) model, a quantitative risk assessment model which is supported by cloud supplier security assessment (CSSA) and cloud supply chain mapping (CSCM). Using the CSCCRA model, we assess the risk of a Customer Relationship Management (CRM) application, mapping its supply chain to identify weak links, evaluating its security risks and presenting the risk value in dollar terms, with this, promoting cost-effective risk mitigation and optimal risk prioritisation.

The great interest for deploying applications in cloud infrastructures is rapidly growing due to its convenience and ease of use. Despite, the large number of different applications migrated to cloud, there are still applications that are not frequently met on cloud infrastructures. Applications defined as time critical or data-intensive are applications of this kind. The need of high resilience alongside with high performance lead these types of applications to run on mainframes, rather than on cloud infrastructures, as cloud is not able to satisfy them under strict Service Level Agreements (SLAs) and without predictable performance. To investigate further this area this paper aims to report on the research issues around time critical and data-intensive applications deployed on cloud and present Mobile Number Portability (MNP) Use Case migration to cloud with predictable performance.

Cyberbullying is omnipresent among all sections of society who have access to the internet. Vast research has been carried out on this topic around the world however there has not been enough research that is New Zealand based. The objective of this research is to identify the characteristics of cyber victims on social media in New Zealand. We scrutinize the prevalence of cyberbullying in New Zealand among university students based on age, gender and personality. The survey was designed stating the hypotheses developed as a result of the literature review. We gathered the data of sample size n = 158. We conclude that students with openness to experience are more likely to be cyberbullied compared to the other personalities. Whereas, we found no correlation of age and gender with the cyber bullying on a university level. The results from this study can have a positive application in counter cyberbullying programs in New Zealand. This study will a give an impetus for further analytical research in the field of cyber bullying in New Zealand.

This paper presents a proposal for the novel comparison tool for bank charges; the online calculator service. The development of this tool was motivated by information asymmetry, which exists on the market of payment accounts to consumer’s disadvantage. Our calculator service provides user with the list of the most suitable bank accounts based on his preferences, sorted by monthly fee. It is up to the particular user whether he fills in values of his current usage or future requirements. The results are personalized based solely on user’s input. This paper reveals motivation behind our work and presents the current implementation of our proposal including conceptual foundation, workflows, matrix of data for underlying logic and of course user interface. By presenting workflows we stress multidimensional use of our service. Apart for clear benefit for individual user, the data acquired from all users can be used for post-processing, which includes various analyses of user behaviour and resulting user profiling regarding using bank services. The calculator service was already launched for Czech environment on https://uni.uhk.cz/kalkulator/ .

This paper investigates the hedonic and utilitarian motivations that may influence UK grocery consumers to adopt and use new features proposed for an in-store mobile app. The scope of this research is to develop a conceptual model that reflects the motivations for using an in-store mobile app to engage customers. Two pilots were conducted to explore possible attributes for hedonic and utilitarian motivations found in literature, and factor analysis was used to test their validity. A survey with the final items selected was used to collect data from a large UK grocery retailer resulting in a sample of 633 customers. The results supported that utilitarian motivations for grocery shopping include time convenience, performance expectancy and information availability. For the hedonic motivations, the attributes supported include idea motivation, personalisation, value motivation and experiential shopping. Although previous research conceptualised user control as an important utilitarian motivator, this research found that this attribute correlates similarly to both, hedonic and utilitarian motivations. Possible implications are that regardless of customers’ hedonic or utilitarian preferences, it is always essential for customers to have the ability to choose and customise what data and communications they share and receive for successful in-store mobile app engagement.

The paper is focused on the comparison and calculation of retail payment accounts. The latest development of digital services within the frame of a FinTech leaves out the product comparison so far and therefore a consumer has to rely on these online tools. Six comparison tools were found and analyzed in two selected countries. The information quality test was performed based on the EU methodology regarding accuracy and full price, relevance, language and concision, detail, uniformity, comparability, and verifiability. The user test profile is a retail mainstream client with e-banking preference. All comparison tools but one failed in the information quality test. Some of them provided a correct result for only 33% of compared offers. Most of the misguiding and incorrect results came from a miscalculation of specific conditional sales issues and ATM withdrawal from other bank’s network service. Only one comparison tool passed with the share of correct and plausible results above 90%. Unsatisfactory results can be explained by the incompleteness of CTs, not being up-to-date issues and by a specific pricing policy different from e.g. United Kingdom or Germany. The last part suggests possible ways how to improve current unsatisfactory situation by creating a test framework that would complement the Directive 2014/92/EU.

The importance of Privacy Ιmpact Αssessment (PIA) has been emphasized by privacy researchers and its conduction is provisioned in legal frameworks, such as the European Union’s General Data Protection Regulation. However, it is still a complicated and bewildering task for organizations processing personal data, as available methods and guidelines fail to provide adequate guidance confusing organisations and PIA practitioners. This paper analyzes the interplay among PIA stakeholders and proposes an organizational scheme for successful PIA projects.

The increasing popularity of social media has led many organizations to find new ways of customer engagement. This paper presents an initial pilot study to explore the affordance of social media in engagement processes. By applying the affordance theory and Porter’s process for engagement model, we used a case study approach to examine the case company’s Facebook and Twitter content to identify the engagement possibilities of social media. Our preliminary results show that social media opens a new channel for organisations to engage with their customers. We present a preliminary theoretical model to understand the how the functional affordances of social media are socialised in engagement processes, which ultimately gives rise to socialised affordances.

The research aim is to investigate the Geographic Information (GI) influence on e-government adoption by citizens and introduce the GI based E-government citizens’ adoption framework (GE-government). A thorough literature review was executed examining how GI is relevant to E-government services and identify the GI aspects that may affect e-government adoption by citizens. The literature review showed no evidence of any published e-government model considering GI as an independent factor having impact on e-government citizens’ adoption. Moreover, it identified the most common E-government adoption influential factors. We studied the GI impact through the GE-government adoption model by assessing its significant influence. The research findings offered an additional value supporting the E-government’s implementers in enhancing the E-government citizens’ adoption. This paper proposes a factor that could affect E-government adoption modelling and has not been identified in the literature, so far. The paper concludes with a proposed framework and outlines future research.

‘E-government’ is an extremely interesting research field, with numerous academic and practical implications. Its empirical investigation gives rise for significant observations, since the existing international literature offers several research gaps. The aim of the present study is twofold: (a) to develop an original conceptual framework (research model) examining the factors that have an impact on the intention to use of e-government services, (b) to empirically test that framework, using primary data collected from non-adopters of e-government located in Greece. The proposed framework is tested using data collected with a newly-developed structured questionnaire in a sample of Greek internet users. The ten independent factors incorporated into the proposed research framework are measured with a series of questions (items) which have been adopted from various other studies found in the international literature. The empirical data are analyzed using the ‘Structural Equation Modeling’ technique. The main findings suggest that Perceived Usefulness, Peer Influence, Computer Self-efficacy, and Perceived Risk are the main factors affecting the intention of non-users to use e-Government services.

For the past decade, agile development approaches have achieved a good level of success. It does appear however that not all development environments have the same level of agile readiness, hence an organization’s prevalent culture may be a mismatch with the agile development approach adopted. In this paper, we report on a structured literature review of information systems development projects that were conducted in a public sector or government organization. We posit that public sector and government organizations are commonly found to be bureaucratic in nature and we investigate how this impacts the project implementation using agile methodology. We document the challenges encountered in implementing these projects and some approaches to resolving these challenges.

Finland is set to take the lead in developing maritime digitalization and autonomous shipping. This transformation rests on transparency efforts by Finnish government, characterized by participatory democracy and co-creation of services in public sector, the end of innovation deficit in public services through introduction of dedicated innovation budgets and open data movement for re-usability purposes. The research employs action research methodology and aims to analyse two forms of transparency driven innovation that took place during 2016–2018 as part of waterway digitalisation initiative by Finnish Transport Agency: ‘Open Data Innovation’ as opening up government processes and data and ‘Open Door Innovation’ approach as transforming service delivery. Both approaches initially resulted in number of innovative services, unintended consequences occurred in later stages of digitalization phase due to the lack of interest from businesses and greater public. We conclude with lessons learned and share recommendations for government to succeed in digitalizing one of the most conservative industries.

Telerehabilitation (TeleRehab) is the modern innovation used for rehabilitation service. Evidence in favor of readiness among healthcare personnel in adopting TeleRehab is limited. Since “readiness” is a crucial prerequisite to the successful implementation of an innovation, studying the healthcare personnel readiness for TeleRehab is mandatory to gain a better understanding of the relationships among the factors. The main aim of this paper is to determine the relationship among the readiness factors of healthcare personnel and to identify the most influential factors from the recommended readiness list with the help of ISM approach. The study has been conducted in three different phases: the identification of readiness factors from reviewing the literature, interviews with personnel healthcare, and determining the relationship among the readiness factors and its most influential factor. Twelve (12) relevant readiness factors have been identified from reviewing the literature and interviews with experts. Through the use of ISM, five (5) factors have been identified as driver factors; another five (5) factors have been identified as the linkage factors and two (2) factors have been identified as the dependence factors. No factor has been identified as autonomous factor. Out of which, one (1) factor has been identified as top-level factor and one (1) bottom level factor. Clear understanding of these readiness factors will help healthcare institutions to better prioritize and manage their human resource, healthcare personnel in an efficient and effective way to adopt TeleRehab. The proposed structured model developed will help to understand relationship of the readiness factors.

The rapid adoption of Electronic Health Record (EHR) systems requires advanced enactment strategies for analyzing medical reports. Indeed, the information presented in these reports is difficult to access and it is onerous to analyze it by medical decision support systems. Medical reports characterize full descriptions of the patient diagnosis process. They bring together information about exam steps such as applied techniques, results, synthesis and medical conclusions. In this paper, we propose a medical report modeling and analyzing approach that aims to analyze medical reports for Magnetic Resonance Imaging (MRI) exams. Ontological model is dedicated to represent information from radiological reports in order to make them comprehensible and machine readable. Moreover, reasoning techniques are used to treat a large amount of clinical data. This provides an analyzing system allowing user to be informed about the evolution of the patient state. The proposed system was successfully applied to a set of Hepatocellular Carcinoma (HCC) medical reports from University Hospital of Clermont-Ferrand (CHU), France.

Current devices and sensors have revolutionized our daily lives, with the healthcare domain exploring and adapting new technologies. The rapid explosion of digital healthcare happened with the help of current 4G LTE technologies including innovations such as the continuous monitoring of patient vitals, teleporting doctors to a virtual environment or leveraging Artificial Intelligence to generate new medical insights. The arised problem is that current 4G LTE based communication platforms will not be able to keep up with the exploding connectivity demands. This is where the new 5G technology comes, expected to support ultra-reliable, low-latency and massive data communications. In this paper, an end-to-end approach is being provided in the healthcare domain for gathering medical data, anonymizing it, cleaning it, making it interoperable, and finally storing it through 5G network technologies, for their transmission to a different location, supporting real-time results and decision-making.

Industry 4.0 (I4.0) is changing business models and processes. I4.0 uses innovative trends such as Big Data, Cloud Computing, and Internet of things (IOT) to maximize economic benefits and return on investments. However, developing an I4.0 project may be costly, complex and risky for some companies. Therefore, careful requirements definition and mature Requirement Engineering (RE) processes are necessary. Undeveloped RE processes and poorly defined business requirements will often result in an inferior or a cancelled project. In addition, to ensure agility and allow for iterative changes in developing projects for I4.0, agile methodologies should be applied and prudently assessed. Unfortunately, most of existing assessment models are narrow focused and lack theoretical foundation and proper validation. This research proposes a comprehensive maturity framework called agile Requirement Engineering Maturity Model for Industry 4.0 (ARE-MMI4.0). The framework provides assessment of the minimum maturity levels to start a project for I4.0. The framework integrates an I4.0 maturity model with RE and agile maturity models to ensure the ultimate maturity assessment for the business processes.

The main goal of this exploratory study is to investigate the role of employees’ age in the perception of factors having an influence on enterprise systems (ES) adoption process. In doing so, the current study draws from opinions of 75 ES practitioners collected during an exploratory research conducted in Poland. The gathered data was analyzed following the grounded theory approach and incorporating open and axial coding. In consequence, a two-level taxonomy of elements including determinants and determinant categories was worked out. Then, the distribution of respondent opinions among different age groups, i.e. younger, middle-aged, and older, was analyzed. The main findings imply that project schedule and employees’ attitudes and involvement are the fundamental determinants emphasized regardless of respondent age. At the same time, older respondents perceived implementation process-related determinants to a greater extent, while the youngest particularly highlighted determinants associated with technology.

This paper presents an early version of a decision-making “eco” system. We refer to it as an “eco” system because it is primarily based on mathematical logic and combines concepts and principles from the fields of statistics, decision theory, artificial intelligence and modeling of human behavior. The primary goal of the proposed approach is to address errors that occur resulting from the misuse of statistical methods. In practice, such errors often occur either owning to the use of inappropriate statistical methods or wrong interpretations of results. The proposed approach relies on the LPwNF (Logic Programming without Negation as Failure) framework of non-monotonic reasoning as provided by Gorgias. The proposed system enables automatic selection of the appropriate statistical method, based on the characteristics of the problem and the sample. The expected impact could be twofold: it can enhance the use of statistical systems like R and, combined with a Java-based interface to Gorgias, make non-monotonic reasoning easy to use in the proposed context.

The study of recommender systems is essential nowadays due to its great effect on businesses and customer satisfaction. Different active learning strategies were previously developed to gain ratings from the users on specific items, and this enables the system to have more information and consequently make more accurate recommendations. In previous studies, these strategies were evaluated using a different selection of metrics in each work, and the experimentations were done on different datasets. In this paper, we solve these weaknesses by comparing the main ten non-personalized strategies on a fair ground, by simulating them against two datasets and using seven of the mostly agreed upon metrics. This gives more trust and less biased results when comparing their performances. Also, the analysis of the computation time and the elicitation efficiency is added.

This paper seeks to present a new dimension to the dimensions of IT governance; it proposes a model for the board interlocking and the IT governance. This conceptual model is based primarily on the Resource Dependence theory and tries to interpret the relationship between the board interlocking and the IT governance. This paper has theoretically reviewed the existing literature of the board interlocking; it has also added to the real gap in the literature of corporate governance which has not explained the importance of the board interlocking with IT governance. The researchers hope to provides a solid foundation for IT governance in order to supply companies with information about the IT environment surrounding it, the operating procedures, and the effective monitoring of the information systems, the challenges they face, the opportunities they may have, and to provide members of the board of directors with neutral opinion about these opportunities and challenges. The paper presents several contributions at both theoretical and practical levels; it paves the way for researchers to discuss the board interlocking with IT governance which contributes to the development of the theories governing the work of these concepts. It also draws the attention of the companies’ administration to one of the most important practices in forming and structuring the board, i.e. the necessity of connecting the board of directors with managers who are qualified with practical experience in information systems.

Some approaches to represent business models can support the analysis of value creation in platform ecosystems and its impact on the business models involved, by improving the understanding of roles, structure and, ideally, risks. This work contributes by providing an integrated overview of business model representations and examines if ecosystem risk analysis is supported, thus providing researchers and practitioners with a deeper insight into suitable tools for understanding digital platform ecosystems and the business models involved.

Recent research on IT Strategy is in a phase of renewal, after a long period of static formal comprehensive planning. Currently, more importance is given to incremental continuous planning, program implementation and organizational learning, what has been labeled as strategy as practice. However, less attention has been paid to the evaluation of the implementation process and results.In this paper, we introduce an exploratory approach for assessing the implementation of IT Strategic planning, based in the combination and iteration of different methods. It is grounded in an Action Design Research exercise recently made up at a leading on-line European university.The assessment includes three major dimensions (strategy, performance and governance), extracted from the academic and professional research. Its application to this context through a varied scaffolding of methods, tools and techniques, that is summarized in the article, seems robust, able to work out with the business and IT senior stakeholders and allows a quick deployment, even in a complex institutional environment.We propose further research in order to extend and validate this model through its implementation and evaluation in different contexts, selecting new variables and metrics, developing improved maturity frameworks and repeating the exercise on a periodical basis.

Agile software development methods are being used on larger projects thus the study of inter-team communication are becoming an important topic of interest for researchers. This research addresses inter-team communication by exploring the tools and three different boundaries, inter-team, team and customers, and geographically separated teams. In this research, we gathered data from semi-structured face-to-face interviews which were analyzed following the grounded theory approach. Our study reveals consensus from different teams on the importance of virtual Kanban boards. Also, some team members tend to adapt to other teams’ preferred communication tool. We observed challenges around interdependent user stories among the different teams and highlighted the problems that rise at the different boundaries.

Strategic Information Systems Planning (SISP) supports business goals and business strategy, through the use of Information Systems (IS). Findings from previous surveys indicate that many managers make too much effort to SISP process while others too little. The implemented plans are not effective, successful and they do not meet the objectives. Researchers have noticed that family businesses focus on business’s long-term sustainability, but they do not develop strategic planning. More attention is needed to be payed to and how they use IS and strategic planning in order to deal with the crisis. The purpose of this paper is to indicate the phases which contribute to a greater extent of success in order to provide conclusions regarding the implementation of this process in SMEs. Data were collected using questionnaires to IS executives in Greek SMEs. Factor Analysis is performed on the detailed items of the SISP process and success constructs.

Czech banking market is specific for its high percentage of earnings from bank charges as a total percentage of bank earnings. This article is focused on the problems associated with bargaining between bank clients and banking institutions in the Czech Republic. With most banks in the market, bank clients must pay monthly charges in order to maintain their bank accounts. The article describes the interaction between the bank and the client from the game theory perspective. Both bargaining parties have different goals and they encounter each other during the bargaining process about the price of bank charges. The game theory defines the pay-off function, the decision tree and the point of conflict. The result is a model of this interaction that appears as an extensive form game. The actual amount of charges that result from the bargaining is regularly ascertained by a national survey using the Client Index (Klientský index) for current accounts in the Czech Republic. The Client Index represents the quantification of average costs of maintaining a current account of individual respondents based on the monitoring of specific retail banking products and services according to fee schedules of individual banks and the behaviour of individual bank clients. The approximation of the value of this Client Index was used for the proposal of pay-off function in the model. The paper also deals with general theoretical bases of bargaining, particularly it focused on bargaining with a client. The cooperative and non-cooperative strategy towards the client are described. The reasons for bargaining with existing bank clients are presented as well. Finally the article also summarizes both the goals of clients and banks during bargaining.

The purpose of this paper is: (1) to analyze the current state of financial reporting standardization; (2) to determine the impact of technical, organizational and environmental factors on the level of adoption of XBRL; (3) to investigate if there was a difference regarding the impact of the these factors on financial companies, and regulatory bodies, in emerging countries, as is Montenegro. Survey’s data and the effect of the variables were tested using the explorative factor analysis. In line with exceptions, results suggest that there is a difference with regard to impact of analyzed factors on degree of acceptance of standardized reporting forms. Environmental factors have the biggest influence, then the technical ones and at the end organizational factors. Obtained findings can serve creators of national financial reporting strategies to understand impact of analyzed factors, properly identify challenges with regard XBRL adoption and better manage with proactive or corrective initiatives.

In this study we applied the technology acceptance model (TAM) to explain users’ acceptance of mobile technology as a medium of knowledge providing. We adjusted the TAM by adding three new constructs: Access to Information, Information Quality, and Information Navigation. The model was tested on a population of 303 respondents using structural equation modeling (SEM). Our findings indicated that information quality and information navigation influence the perceived ease of use and, as a result, perceived usefulness of mobile technology usage that has an impact on the behavioral intention of use and the actual use of these devices. The developed model might comprise the basis for further research in the area of mobile technology usage for knowledge providing.