Open and Big Data Management and Innovation

Governments have always retained public service data internally in their own systems with only limited information provided to the public and other stakeholders such as the business, charitable and NGO communities. However, the rapid advancement of ICTs coupled with electronic publishing via the Internet in the last decade in particular has enabled governments to exploit the potential of wider distribution and use of such data previously held in internal systems. The panellists will discuss how Big, Open and Linked Data (BOLD) can be utilized to drive innovation and what obstacles and challenges may be encountered. Empowering citizens, potential mis-use in identity theft, policy manipulation or market distortion, and the need to combine open data with closed sources will be discussed.

This study aims to explore whether Jordanian customers’ perceptions on intention and adoption of Mobile banking (MB) services varies according to their demographic characteristics. As per the prior literature, five demographic factors, namely age, gender, income, education and customer’s experience with computer and Internet have been considered in the current study. The required data were collected from the field survey questionnaires administered to a convenience sample of Jordanian banking customers. The major statistical results (mean and standard deviation) demonstrate that the customers’ perceptions on intention and adoption of MB are likely to vary due to customers’ demographic differences. According to the current study’s findings, it was also noticed that despite the fact that the most of the sample respondents express a high intention to adopt MB, the adoption rate for the majority of MB services was low.

The population is rapidly ageing in countries such as Finland. However, little research has been conducted to better understand older travellers’ use of Internet and mobile devices. This qualitative study aims at exploring young-elderly (aged 60-75) travellers as potential users and actual users of the Internet with mobile device during trips. The results identify a range of possible drivers and barriers for the use of Internet with mobile devices and their impact on the travel experience during trips. The study also suggests that there is a substantial number of young-elderly travellers that are quite advanced in their mobile usage behaviour.

Online household e-waste collection services are emerging as new solutions to disposing household e-waste in China. This study aims to investigate the adoption of online household e-waste collection services in China. Based on the previous technology diffusion theories (e.g., TAM, UTAUT), a research model with six research hypotheses was proposed in this research. The research model was empirically tested with a sample of 203 users of online household e-waste collection services in China. The results indicated that five of the six research hypotheses were significantly supported. And the most significant determinant for the behavioral intention to use online household e-waste service was effort expectancy. However, facilitating condition did not have significant impact on users’ behavior of using online household e-waste collection services.

This paper presents the first stage of an investigation work whose purpose is to introduce a new form of communication between the school and the family, through an electronic record (ER). We tried to identify, with a questionnaire, the perceptions of Teachers and Guardians towards the adoption of an ER. Both groups underlined the importance of communication between the school and the family, and expressed interest in the ER, as a communicational tool.

In this paper, we examine cryptocurrencies as a potentially disruptive sort of payment method. Due to its relative importance, we focus in particular on Bitcoin. Through an inductive, exploratory interview approach with 13 individuals in three distinct groups, the determinants usability, usefulness, and subjective norm that could make Bitcoin a game-changer are explored. The results reveal that most stakeholders consider perceived ease of use still rather low, with perceived usefulness varying according to the user group. The notion of Bitcoin as having much future potential as a payment method is confirmed across all interviewees. Interestingly, the underlying concept of a blockchain is also seen as a potential revolutionary way to create a more just society based on open platforms and open data. However, the reasons of why Bitcoin is actually a disruption to existing solutions varies widely.

The Internet of Things (IoT) has high promises and might provide many benefits, yet has been given scant attention in e-government literature. Within the IoT, physical objects, “things”, are networked and connected to the Internet. These “things” are able to identify themselves to and communicate with other devices or “things”. There are many impediments blocking the adoption of IoT, and there is limited insight in these barriers. In this paper, impediments for the adoption of IoT are investigated by conducting a literature review and carrying out two case studies. The impediments found in literature were confirmed and extended using the case studies. Results show that impediments are interrelated and occur on the strategic, tactical and operational level. For adoption the impediments needs to be addressed in concert. Research on e-governance can benefit from understanding these interrelated impediments.

Utilising Mobile Internet (M-Internet) services would increase socio-economic benefits. Hence, it is necessary to consider the factors that may increase the adoption of M-Internet services within the context of Saudi Arabia. This research aims to examine potential users’ intentions towards different variables that may be significant for supporting higher usage of M-Internet services in the domain of the Kingdom of Saudi Arabia. This study embraces the following variables: perceived risk, innovativeness; performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value, hedonic motivation and behavioural intention. Data was collected by means of a questionnaire on a convenience sample that consisted of 600 subjects with a response rate of 69.5%. The findings gathered from a descriptive analysis suggested that the related variables are perceived as significant by participants and they have strong behavioural intention to use M-Internet services.

A growing number of companies are recognising the benefits of using social media in customer relationship management. At the same time, the consumers’ expectations are rising: short response times, individual communication, real interaction with humans, and participation. It is a challenge to observe the many different user activities on many different social media sites. The aim is to reduce the complexity of integrating multiple social media sites with enterprise systems. Therefore, a conceptualisation of user activities in social media is presented. A user activity is a cross-over of an action invoked on an object and a user who acts in a certain context. The 40 user activity types are compared with actual features of ten social media sites. We find out that a substantial share of them can be integrated technically using the social media site’s Application Programming Interfaces (APIs).

As using online services penetrates deeper in our everyday life, lots of trust-sensitive transactions are carried out electronically. In this regard, a big challenge is to deal with proper user authentication and access control without threatening the users’ privacy. However, commonly used strong authentication schemes fail to address important privacy requirements. In this paper, we focus on an emerging type of digital certificates, known as Privacy-preserving Attribute-based Credentials (Privacy-ABCs), which allow privacy and security go hand-in-hand. So far, there has been no systematic study on the potential factors that have influence on the adoption of Privacy-ABCs by service providers. Thus, we developed a conceptual model of the relevant factors based on well-established theories and our practical experience with trialing Privacy-ABCs, and evaluated the model through expert surveys.

This study aims to examine the factors that affect consumer adoption of social commerce technologies in the context of Saudi Arabia. The factors descriptively explored in this research include: performance expectancy, effort expectancy, social influence, hedonic motivation, habit, trust, consumer innovativeness, information quality and behavioural intention. The survey data utilised in this research was collected through a self-administered questionnaire within a convenience sample. The results obtained through a descriptive analysis confirmed that Saudi consumers perceive the abovementioned factors as important and they have strong behavioural intention to use social commerce technologies.

Operational business intelligence (OpBI) integrates data of business processes to analyse their performance in relation to organizational goals. The consequent decision-making concerns a timely recognition and execution of actions to maintain performant business processes. OpBI systems can be designed according to a firm-specific definition of requirements guided by considerations from business model, business process and information system perspective. However, there is no approach to link the design of OpBI jointly with characteristics of business models and business processes, yet. The paper uses therefore an action research method and proposes a business approach that combines e

3

3value with the work system framework to set up conceptual application designs for an OpBI-reliant decision support. We report on results of a long-term research project to demonstrate the development and application of our approach in four different business scenarios. The findings include implications towards a business-oriented application design of OpBI systems.

Today’s rapidly changing and highly regulated business environments demand that organizations are agile in their decision making and data handling. At the same time, transparency in the decision making processes and in how they are adjusted is of critical importance as well. Our research focusses on obtaining transparency by not only documenting but also enforcing data governance policies and their resultant business and data rules by using a multi-level metadata approach. The multi-level approach makes a separation between different concerns: policy formulation, rule specification and enforcement. This separation does not only give more agility but also allows many different implementation architectures. The main types are described and evaluated.

Similarity search in the big data environment is a challenging task. Patient Similarity search (PaSi) is an important issue in healthcare network and data. The results of PaSi search may be highly useful for drawing different conclusions and decisions to improve healthcare systems. Such findings can also be useful for choosing the treatment paths for new patients. In this paper, we propose a MapReduce based framework as a solution to the PaSi problem in the context of a healthcare network imagined to be implemented considering the healthcare centers of India. It is assumed that such a healthcare network will be implemented in future over the Government of India cloud known as GI cloud or ‘MeghRaj’. The paper also discusses the associated implementation challenges of the proposed framework and the query handling approach for the proposed framework to solve the PaSi problem is stated. Finally, the paper outlines the future scope of the work.

Facebook, Twitter, Instagram, and other players in the social media world have been on the rise during the last couple of years. In contrast to their popularity, their underlying business models are vague and often only linked to advertising. In this explorative study we identify new revenue sources for social media service providers besides advertising. Based on three use cases with Facebook, Tencent, and LinkedIn, we identify three possibly fruitful ways to extend existing social media business models. Subsequently, a survey with 301 respondents changes perspectives on the user’s willingness to pay in order to identify usage-related differences evoked by cultural and external circumstances. Four derived hypotheses lead the way to avenues of further research especially in terms of Big Data analytics with new e-commerce trends like Facebook’s Buy Button.

This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture (BASOA), and applying BASOA to business intelligence, where our surveyed data analysis showed that the proposed BASOA is viable for developing business intelligence and enterprise information systems. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

Linking open data in government domain, can lead to creation of new services and information as well as discovery of new ways to perform queries and get results in accessible, machine processable and structured manner. To reach the full potential of open government data more relations between data should be discovered. The interconnection of open government data and semantic description of their relations can bring new aspect of producing and consuming the data. In this paper we investigate issues for producing and utilizing open government data with special focus on dataset relations. We have proposed the Linked Relations (LIRE) architecture for relations creation between datasets and a basic RDF model of relation between two datasets. The architecture contains different modules that perform analysis of datasets attributes and suggest the type of relation between the datasets. It can be utilized by open data portals for creating relations between datasets belonging to different public agencies and government sectors. An idea presented in this paper is made available as CKAN plugin.

Governments are under pressure to meet new social demands and seek new forms of management. As well as this, the fact that they make considerable use of information technology, has led to the growth of their databases, and made governments and the respective government organizations, fertile ground for open data initiatives. Having access to budgetary data and being able to make use of it (with regard to revenue and expenditure), has traditionally always aroused great interest in society. The purpose of this study is to determine the potential benefits and possible obstacles that can affect the intermediaries who take action on the basis of budgetary data. A number of intermediaries (members of society and government policymakers) from four Latin-American countries were interviewed. The results show that the structural barriers of governments have an adverse effect on their activities because they impair the quality of the information that is made available. Nonetheless, the benefits that allow a greater degree of transparency as well as the ability to reveal more knowledge of the inside operations of governments, encourage the intermediaries to take part in this “ecosystem”.

Although one of the main reasons to open data by governments is to create a transparent government, many initiatives fail to deliver transparency. Making data available does not automatically yield up transparency. Furthermore transparency is an ill-defined concept and understood in different ways. Added on this puzzle, Big Data Analytics are becoming reality in governments and on society due the quantity of open data available and the evolution of techniques and instruments used to analyze data. This paper develops a Big and Open Linked Data (BOLD) Framework identifying categories, dimensions and sub-dimensions that influence transparency. Our framework conceptualizes transparency as a process of data disclosure and usage. Transparency is based on the two major synonymous concept used on literature, namely accountability and openness. Accountability means revealing important details for transparency to control governments financially and operationally, whereas openness reveals details of what, how and why politics took the decision, without revealing important parts of the political game inside government such in military and nuclear area.

Governments are producing significant public data that, if made open, is expected to create enormous social and commercial value as well as improve the civil governance. Unleashing the true power of open public data requires a much better understanding of its ecosystem than is known currently. This paper surveys the global open data landscape by taking into account the Open Data Barometer (ODB) ranking system and its three sub-indexes - readiness, implementation and impact. These indexes are compared and analyzed on the basis of income levels of the ODB ranked countries. Finally, using air quality open data, data availability in developing countries like China is compared with countries of better practices such as UK and US. The comparison helps in understanding the current situation and barriers in opening data in China.

Governments across the world are releasing public data in an effort to increase transparency of how public services are managed whilst also enticing citizens to participate in the policy decision-making processes. The channel for making open data available to citizens in the UK is the data.gov.uk platform, which brings together data relating to various public services in one searchable website. The data.gov.uk platform currently offers access to 25,500 datasets that are organized across key public service themes including health, transport, education, environment, and public spending in towns and cities. While the website reports 5,438,159 site visits as of June 2015, the average time spent on the site has been recorded at just 02:12 min per visitor. This raises questions regarding the actual use and usability of open data platforms and the extent to which they fulfill the stated outcomes of open data. In this paper, the authors examine usability issues surrounding open data platforms and propose a framework that can be used to evaluate their usability.

Crowdsourcing has become an increasingly attractive practice for companies to execute business processes in open contexts with on-demand workforce and higher level of flexibility. One of the challenges is the identification of the best-fit crowdsourcing participant from a group of online candidates. This paper presents a method of AHP-TOPSIS based on Grey Relation Analysis for estimating participants of a crowdsourcing task based on their online profiles and proposals. This method is tested by an experiment on a dataset of 348 completed IT service crowdsourcing tasks. An analysis on the matching between the test result and the actual selection result reveals the accuracy and efficiency of this method. Companies can use this method to facilitate the quality control at the beginning of crowdsourcing and keeps the selection of participants easy. This paper contributes to the design of a software agent for crowdsourcing platforms to automatically rank the participants of a task.

Evidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of these environments. As FLOSS repositories store data about participants’ interaction and activities, we analyze participants’ interaction and knowledge exchange in emails to trace learning activities that occur in distinct phases of the learning process. We make use of semantic search in SQL to retrieve data and build corresponding event logs which are then fed to a process mining tool in order to produce visual workflow nets. We view these nets as representative of the traces of learning activities in FLOSS as well as their relevant flow of occurrence. Additional statistical details are provided to contextualize and describe these models.

While in early years, software technology companies such as IBM and Novell invested time and resources in open source software (OSS) development, today even user firms (e.g., Samsung) invest in OSS development. Thus, today’s professional OSS projects receive contributions from hobbyists, universities, research centers, as well as software vendors and user firms. Theorists have referred to this kind of combined public and private investments in innovation creation as private-collective innovation. In particular, the private-collective innovation model seeks to explain why firms privately invest resources to create artifacts that share the characteristics of non-rivalry and non-excludability. The aim of this research is to investigate how different contributor groups associated with public and increasing private interests interact in an OSS development project. The results of the study show that the balance between private and collective contributors in the Linux kernel development seems to be changing to an open source project that is mostly developed jointly by private companies.

Managing outsourcing processes requires a retained organization to orchestrate an organization’s IT functions into a concerted whole. Nowadays multiple outsourcing vendors need to be managed. The purpose of this research is to identify capabilities affecting orchestration of outsourced IT functions. An existing framework for outsourcing capabilities is used as a starting point. Due to the scarcity of research a qualitative research approach based on two case studies is taken. The findings shows that the core IS capabilities as found in the literature are found to be too abstract, ambiguous and that several essential capabilities are missed. A framework containing a refined and extended set of capabilities is derived. Four new capabilities were found including: demand, financial, (service) delivery and service portfolio management.

The increased use of the freemium business model and the introduction of new tools have made analytics pervasive in the video game industry. The research on game analytics is scant and descriptive. Thus, reasons for employing game analytics are not well understood. In this study, we analyze data collected with a set of in-depth interviews from small and medium-sized freemium game developers. The results show that game analytics is used to (1) assist design, (2) to reduce the risks associated with launching new games, and (3) to communicate with investors and publishers. The study advances the research on the business value of game analytics.

Management scholars are criticized for ignorance and the wrong approach when studying the impact of technology in organizational life. Impact of technology in this paper is interpreted as IT values created or achieved from equivalent and contingent interaction between human (people) and non-human agents (technology, organization). Researchers and theorists propose to include a sociomaterial perspective and to develop general and broader, empirical based patterns across different contexts. Based on a literature review containing publications of theoretical considerations and empirical research this paper introduces a first general and sociomaterial based overview and taxonomy of IT values and their relations. IT values have a techno-economic or socio-techno orientation, are dynamically entangled and competitive, and complementary or overlapping. IT values are related to time, sponsor and, hierarchy. The identified IT values are ordered into a framework which has to be treated as a starting point to discuss further the definition, dynamics and relations of IT values from a sociomaterial perspective.

Advances in data semantification and natural language querying are enabling new generations of context-aware mobile applications. Such applications would rely on platforms that integrate heterogeneous sets of user data from a range of applications and systems. Designing these platforms is challenging as they should serve multiple user groups at the same time. In this paper, we analyze who should subsidize multi-sided data platforms that enable mobile context-aware travel applications. After analyzing the different user groups and revenue models, we assess end-user acceptance of these revenue models through a survey among 197 potential users. Results show that users willing to share data with app developers are more inclined to use data-driven mobile travel apps but are less inclined to pay for them. This paradoxical result explains why premium-pricing as well as data-monetization strategies can both be viable.

The e-service concept has been a central concern in many research and practitioner areas in recent years. There are expectations of citizens, customers, commercial companies and public organizations of what e-services are, their functionality and benefits. However, there is conceptual confusion that may hamper collaboration and research viability. This paper explores the conceptual vagueness and presents an empirical investigation of how the e-service concept is treated in practice, along with its kindred concept “IT service”. Results show that public and commercial organizations approach e-services differently, that translation problems can cause lack of comparability in research results, and that additional concepts may be introduced instead of e-service.

In the recent years, social media have rapidly gained an increasing popularity. Companies have recognised this development and anticipate advantages from using social media for commercial purposes. Social customer relationship management (CRM) professionalises the use of social media and aims at integrating customers into operational procedures. This induces changes of existing structures, e.g. culture and organisation, business processes, information systems (IS), data structures, and technology. The intended transformation from CRM to social CRM is a complex task, because different aspects are affected, which also are mutually dependent. A prerequisite for the successful implementation of social CRM is understanding these aspects and its dependencies. Separation of concerns is a useful means of addressing complexity. The conglomeration of different issues is dissolved by conceptualising components and its relationships. This paper separates the concerns of social CRM using architectural perspectives and aims at building a better understanding. The research method is a literature review in which artefacts are gathered and assigned to five layers, which are business, process, integration, software, and technology. The conclusion states that social CRM is an emergent research field and comprises a call for more artefacts that concretise abstracted components of the business-layer.

Information sharing across the public sector is a precondition for innovation. The reality today is that data are scattered throughout administrative services. Creating government-to-government (G2G) information systems (IS) has the potential to sustain fluent data flows. Despite this potential, G2G IS projects fail to deliver the expected benefits. Factor research partially explains why so many G2G information systems fail. In this paper we take a broader perspective by applying process research to study six recurrent problems of Flemish G2G IS in their dynamic context. We test whether Sauer’s needs and support-power analysis can provide additional management insights concerning G2G IS projects. Our results, based on interviews and focus groups, show that seemingly controllable problems have much deeper roots that require managers’ action.

Factors found to influence the adoption of ICT have been explored in several studies. However, few writers have been able to produce any systematic research into the digital divide. Although, differences of opinion still exist, a growing body of literature has established that income and education are positively related to digitalization patterns. This research attempts to deepen the understanding of the present ambiguous relationship between socio-economic indicators and the ICT. This account tested the links between socio-economic variables (GDP per capita, GINI index, World Bank Education Statistics, and Transparency International’s corruption perception index) and ICT diffusion across developed and developing countries. Positive correlations were found for income and ICT, education and ICT. A negative correlation was found between corruption and ICT adoption. The paper discusses implication of these findings and suggests future courses of actions for policy makers. Proceeding from the findings of this paper, this research suggests there is an urgent need to address the digital divide by initiating impactful efforts to reduce it.

The online shopping is increasing rapidly because of its convenience to buy from home and comparing products from their reviews written by other purchasers. When people buy a product, they express their emotions about that product in the form of review. In Indian context, it is found that the reviews contain Hindi text along with English. It is also found that most of the Hindi text contains opinionated words like

bahut

achha

,

bakbas

,

pesa

wasool

etc. We have tried to find out different Hindi texts appearing in product reviews written on Indian E-commerce portals. We have also developed a system which takes all those reviews containing Hindi as well as English texts and find out the sentiment expressed in that review for each attribute of the product as well as a final review of the product.

Data analytics promises to detect behavioral patterns, which may be used to improve decision making. However, decisions need to motivated, and they are often motivated by models. In this paper we explore the interplay between data analytics and process modeling, specifically in normative settings. We look specifically at value nets, mathematical models of the flow of money and goods, as used in accounting. Such models can be used to analyze the proportions of various flows, such as resources consumed and products produced. Such analyses can be used in the planning and control cycle, for forecasting, setting a budget, testing and possibly adjusting the budget. In other words, it can be used for adaptive normative modeling. We look in particular at a case study of a provider of public transport services for school children. The case shows that the use of value nets for analysis of proportions is (i) feasible, and (ii) useful, in the sense that it provides valuable new insights about the revenue model.

Cloud computing proved to offer flexible IT solutions. Although large enterprises may benefit from this technology by educating their IT departments, SMEs are dramatically falling behind in cloud usage and hence lose the ability to efficiently adapt their IT to their business needs. This paper introduces the project idea of the H2020 project CloudSocket, by elaborating the idea of Business Processes as a Service, where concept models and semantics are applied to align business processes with Cloud deployed workflows. Four architectural building blocks proposed for (i) design, (ii) allocation, (iii) execution and (iv) evaluation are discussed before providing and outlook.

This paper is the introduction to the fourth Workshop on

IT

 − 

enabled

Resilient

,

Seamless

and

Secure

Global

Supply

Chains

(WITNESS 2015). In the paper, we present a synthesis of the innovation agendas of a series of international research, development and demonstration projects that seek to make supply chains more efficient and more secure. From this agenda, we highlight three main innovation areas that are central to the current transition in the domain of logistics and international trade. Against this background, we introduce the five papers that are part of the WITNESS 2015 workshop. The papers primarily cover IT related innovations and include topics such as data quality and data governance, the development and interoperability of platforms that together present an IT innovation in international trade, and serious gaming for making key players aware of the potential of the innovations. We finalise with the suggestion to put more emphasis on the non-technical parts of the innovations, as that is what is ultimately needed to ensure wide uptake of the innovations, in order to make them really count.

In many of today’s enterprises, data management and data quality are poor. Over the last few years, a new solution strategy has emerged, known as data governance: an overarching methodology that defines who is responsible for what data at what point in a business process. Although positive effects on the business performance and compliance of enterprises are seen in practice, a substantiated method for determining the effects of data governance has not yet been developed. This paper reports on explorative research to develop such a specification method. Through a conceptualization of data governance based on literature, case study analysis of clients of a large consultancy firm and interviews with representatives of companies that have recently implemented data governance, an effect specification framework was developed. Using the interviews, initial steps towards validation were performed.

With increasing international trade and growing emphasis on security and efficiency, enhanced information and data sharing between different stakeholders in global supply chains is required. Currently data quality is not only problematic for traders, but also for various government agencies involved in border control, such as customs authorities and border force. We adapt principles from value cycle modelling in accounting, and show how these principles enabled by ICT can be extended to supply chain management to ensure quality of data reported to customs. We then describe a typical application scenario based on a real but anonymsed case to show that value cycle monitoring can be applied (feasibility), and if applied, what the expected benefits are (usefulness).

Interoperability in logistics is a prerequisite for realizing data pipelines and the Physical Internet. Forecasting data, real time data, and actual positions of shipments, containers, and transport means shared via events have to be harmonized and are expected to improve all types of processes, support synchromodal planning, and improve risk analysis from a compliance and resilience perspective. Technically, several solutions are implemented by organizations and innovations have been validated in so-called Living Labs or demonstrators in various projects. These solutions do not yet provide open systems required for a (global) data pipeline. A federation of solutions is required to construct data pipelines and to support sustainable development of applications on smart devices allowing Small and Medium sized Enterprises to collaborate. This paper proposes a set of platform services and so-called platform protocols to allow interoperability of different platforms for constructing a data pipeline. The proposed services and protocols further extend existing interoperability solutions and services for supply and logistics.

This paper reports on the use of key design properties for development of a new approach towards a solution for sharing shipping information in the supply chain for international trade. Information exchange in international supply chain is extremely inefficient, rather uncoordinated, based largely on paper, e-mail, phone and text message, and far too costly. This paper explores the design properties for a shared information infrastructure to exchange information between all parties in the supply chain, commercial parties as well as authorities, which is called a Shipping Information Pipeline. The contribution of the paper is to expand previous research with complementary key design properties. The paper starts with a review of existing literature on previous proposed solutions for increased collaboration in the supply chain for international trade, Inter-Organization Systems and Information Infrastructures. The paper argues why the previous attempts are inadequate to address the issues in the domain of international supply chains. Instead, a different set of key design properties are proposed for the Shipping Information Pipeline. The solution has been developed in collaboration with a network of representatives for major stakeholders in international trade, whom evaluate it positively and are willing to invest, develop and test the prototype of the Shipping Information Pipeline.

Improving both efficiency and security in international supply chains requires a new approach in data sharing and control measures. Instead of managing supply chain risks individually, supply chain partners need to collaborate in order to exchange cargo information and implement control measures on the level of the entire supply chain. Governmental agencies, having access to this up-to-date and complete information, can implement alternative risk assessment policies, resulting in less disruptive ways of supervising entire trade lanes. However, this paradigm shift requires awareness of these supply chain visibility concepts and increased collaboration between partners in a value chain. In order to disseminate these new concepts and initiate cooperation between key stakeholders, a serious game called ‘The Chain Game’ was designed, implemented and evaluated.