| 61. |
- Osman, Ahmed M. Shahat
(författare)
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Smart Cities and Big Data Analytics : A Data-Driven Decision-Making Perspective
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The phenomenon of digitalization has led to the emergence of a new term—big data. Big data refers to the vast volumes of digital data characterized by its volume, velocity, variety, veracity, and value. The accumulation of enormous amounts of digital data has encouraged academics to develop appropriate technologies and algorithms to manage and analyze these data in order to leverage the embedded relationships within the data to support decision-making. This approach has revolutionized the organizational strategies of most business areas by digitally transforming business operations and decision-making processes.A “smart city” is a new concept that depends primarily on digitization and big data analysis. The aim of a smart city is to tackle the challenges of ever-increasing urbanization by utilizing atypical approaches. The utilization of big data analysis in smart cities has been investigated thoroughly in the literature from various aspects, such as those related to recommended technologies and the domains of applications. A smart city is a compound system with multi-domain attributes in which the citizens represent key participants in decision-making. However, harnessing big data analysis to support decision-making in the smart city context is rarely approached in academia. The infrequency of this type of research was sufficient to motivate this interesting research. Two research questions drive this thesis: RQ1: What are the challenges of utilizing big data analytics (BDA) to enable decision-making in smart cities? RQ2: What are the design principles of the BDA framework in the context of smart cities? To address these research questions, numerous research methods were applied, including a systematic literature review, design science research, use case, and case study. In addition, internationally acknowledged information systems databases were searched to collect quality scholarly articles and conference proceedings: ACM Digital Library, IEEE, SCOPUS, Springer Link, INSPEC, INSPEC, and Web of Science. A freely published dataset for experimental purposes on Yelp (www.yelp.com) was used for the use case experiment. Lastly, the case study was based on data from a national Egyptian digital transformation project called Nafeza.The research findings revealed the need to introduce an inventive framework for exploiting big data analysis in smart city applications. The main contribution of this research is the proposal of a novel framework for utilizing big data analytics in smart cities. The proposed framework, the Smart Cities Data Analytics Panel (SCDAP), is a domain-independent big data analysis framework. It compiles the relevant design principles mentioned in the literature, particularly those that are distinctive to smart cities. The design principles of SCDAP are founded on the literature review, use case, and case study methodologies and are the main contribution of this research.As the four papers that formed the foundation of this thesis combine theoretical and practical research, the contributions of this research can be of direct benefit to academic researchers in this field and practitioners of smart city projects.
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| 62. |
- Padyab, Ali
(författare)
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Exploring Impacts of Secondary Information Use on Individual Privacy
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Information collected from individuals via online social networks and Internet of things devices can be used by institutions and service providers for different business purposes to tailor and customize their services, which is defined as secondary use of information. Although the literature on secondary use is well developed, prior studies have largely focused on direct use of information such as those instances of information use that do not stem from data mining. Advances in data mining and information-processing techniques facilitate discovery of customers’ and users’ behaviors and needs. Research shows that individuals’ behavior can be inferred with high accuracy from their shared information, which may in turn jeopardize privacy. A recent scandal of Cambridge Analytica using about 87 million Facebook profiles to target those users with customized micro-targeted political ads has created public outrage and raised criticisms of secondary use. Given this background, the purpose of this thesis is to explore impacts of organizations’ and service providers’ secondary use of personal information in order to draw conclusions related to how individuals’ attitudes are formed and what role secondary use plays in managing privacy.This research investigates user awareness and attitudes towards potential secondary uses of information. To pursue this, a multi-method qualitative approach using a descriptive questionnaire with 1000 European citizens and a total of 10 focus groups with 43 participants was employed. A qualitative content analysis using both inductive and deductive approaches was conducted to analyze the results. The conceptual framework employed in this thesis was genres of disclosure.The research results suggest that user awareness of the potential for indirect personal information disclosure was relatively low. It was consequently found that participant attitudes toward privacy and disclosure shifted from affective to cognitive when they experienced firsthand the potential inferences that could be made from their own data. Generally, the participant users only considered their direct disclosure of information; through observing potential indirect inferences about their own shared contents and information, however, the participants became more aware of potential infringements on their privacy.The study contributes to information privacy and information systems literature by raising understanding of the impacts of secondary use, in particular its effects on individual privacy management. In addition, this thesis suggests that information privacy is affected differently by direct and indirect uses. Its contribution to information privacy research is to complement previous methodological approaches by suggesting that if users are made aware of indirect inferences that can be made from their content, negative affective responses decrease while cognitive reactions increase through the processing of information related to their disclosure genres. The reason is that indirect use of information inhibits the negotiation of information privacy boundaries and creating unresolved tensions within those boundaries. Cognitive awareness of inferences made to individual information significantly affects the privacy decision-making process. The implication is that there is a need for more dynamic privacy awareness mechanisms that can empower users by providing them with increased awareness of the indirect information they are sharing.
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| 63. |
- Padyab, Ali, et al.
(författare)
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Exploring the dimensions of individual privacy concerns in relation to the Internet of Things use situations
- 2018
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Ingår i: Digital Policy, Regulation and Governance. - : Emerald Group Publishing Limited. - 2398-5038. ; 20:6, s. 528-544
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The integration of internet of things (IoT) devices into daily life introduces challenges for the privacy of their users and those who are affected by these devices. This paper explores the factors that affect individual concerns regarding IoT use and how those factors affect the dynamics of privacy management with the presence of an IoT device. Design/methodology/approach: Four focus groups of individuals and IoT experts were studied to understand the groups? privacy concerns. The authors adopted a qualitative research method based on grounded theory to find relevant dimensions of situational privacy concerns in IoT use situations. Findings: The results revealed that fourteen dimensions of individuals? privacy concerns regarding the IoT are relevant and can be categorized under four key influential factors: collection, IoT device, collected data storage and use of collected data. The authors also analyzed the focus groups using genres of disclosure theory and explored how privacy concerns affect individual privacy management regulations. Research limitations/implications: This paper contributes to how future research can employ genres of disclosure as a theoretical framework to identify situations where privacy violations occur. Practical implications: This study can assist service providers and IoT manufacturers in deriving design principles and decreasing concerns by addressing the information that must be communicated to their users. Originality/value: As opposed to the previous research, which was more inclined to dispositional privacy concerns, this study provides insights into situational privacy concerns when individuals are confronted with the IoT. This study represents the first attempt to investigate the process individuals experience in managing their privacy.
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| 64. |
- Padyab, Ali, et al.
(författare)
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Facebook Users Attitudes towards Secondary Use of Personal Information
- 2016
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Ingår i: Proceedings of the Thirty Seventh International Conference on Information Systems. - 9780996683135 ; , s. 1-15
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Konferensbidrag (refereegranskat)abstract
- This paper reports on a study of how user attitudes to institutional privacy change after exposing users to potential inferences that can be made from information disclosed on Facebook. Two sets of focus group sessions with Facebook users were conducted. Three sessions were conducted by demonstrating to the users, on a general level, what can be inferred from posts using prototypical software called DataBait. Another set of three sessions let the users experience the potential inferences from their own actual Facebook profiles by using the DataBait tool. Findings suggest that the participants’ attitudes to secondary use of information changed from affective to cognitive when they were exposed to potential third-party inferences using their own actual personal information. This observation calls for more research into online tools that allow users to manage and educate themselves dynamically about their own disclosure practices.
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| 65. |
- Padyab, Ali Mohammad, et al.
(författare)
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Adoption Barriers of IoT in Large Scale Pilots
- 2020
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Ingår i: Information. - : MDPI. - 2078-2489. ; 11:23, s. 1-23
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Tidskriftsartikel (refereegranskat)abstract
- The pervasive connectivity of devices enabled by Internet of Things (IoT) technologies is leading the way in various innovative services and applications. This increasing connectivity comes with its own complexity. Thus, large scale pilots (LSPs) are designed to develop, test and use IoT innovations in various domains in conditions very similar to their operational scalable setting. One of the key challenges facing the diffusion of such innovations within the course of an LSP is understanding the conditions in which their respective users decide to adopt them (or not). Accordingly, in this study we explore IoT adoption barriers in four LSPs in Europe from the following domains: smart cities, autonomous driving, wearables and smart agriculture and farming. By applying Roger’s Diffusion of Innovation as a theoretical lens and using empirical data from workshops and expert interviews, we identify a set of common and domain specific adoption barriers. Our results reveal that trust, cost, perceived value, privacy and security are common concerns, yet shape differently across domains. In order to overcome various barriers, the relative advantage or value of using the innovation needs to be clearly communicated and related to the users’ situational use; while this value can be economic in some domains, it is more hedonic in others. LSPs were particularly challenged in applying established strategies to overcome some of those barriers (e.g., co-creation with end-users) due to the immaturity of the technology as well as the scale of pilots. Accordingly, we reflect on the theoretical choice in the discussion as well as the implications of this study on research and practice. We conclude with providing practical recommendations to LSPs and avenues for future research
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| 66. |
- Padyab, Ali Mohammad, et al.
(författare)
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Awareness of Indirect Information Disclosure on Social Network Sites
- 2019
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Ingår i: Social Media + Society. - : Sage Publications. - 2056-3051. ; 5:2
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Tidskriftsartikel (refereegranskat)abstract
- This research investigates user awareness and attitudes toward potential inferences of information posted on social network sites (SNSs). The study reports how user attitudes change after exposure to inferences made based upon information they have disclosed on an SNS, namely, on Facebook. To demonstrate this, two sub-studies involving three focus group sessions were conducted with Facebook users. In the first sub-study, the users received a general introduction to information that can be inferred from posts by using a prototypical privacy-enhancement tool called DataBait. Then, the second sub-study allowed the users to witness the potential inferences of their own Facebook photos and posts by using the DataBait tool. Next, qualitative content analysis was conducted to analyze the results, and these showed that the participants’ attitudes toward privacy on SNSs changed from affective to cognitive when they became aware of potential inferences from actual information posted on their own Facebook accounts. The results imply that end users require more cognitive awareness regarding their genres of disclosure and the effect of their disclosures on their privacy. Moreover, as privacy awareness is contextual, there is a need for more research and development of online tools that will allow users to manage and educate themselves.
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| 67. |
- Padyab, Ali, et al.
(författare)
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Privacy Enhancing Tools: A Literature Review on End-User Role and Evaluation
- 2017
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Ingår i: Proceedings of the Eleventh International Symposium on Human Aspects of Information Security & Assurance (HAISA 2017). - Plymouth : University of Plymouth Press. - 9781841024288
-
Konferensbidrag (refereegranskat)abstract
- Trends show that privacy concerns are rising, but end users are not armed with enoughmechanisms to protect themselves. Privacy enhancing technologies (PETs) or morespecifically, tools (PET-tools) are one of the mechanisms that could help users in this sense.These tools, however, reportedly have low adoption rates, and users tend to be reluctant tointegrate them into their daily use of the Internet. Detailed scrutiny of current research onPET-tools, however, can guide future research to help overcome low adoption of these tools.We conducted a literature review on PET-tools to enumerate the types of tools available andhow they are being evaluated, in order to shed more light on the missing elements in theirevaluations. We reviewed and coded 72 articles in the PET-tool literature. Our resultshighlight two important issues: 1. Evaluation of most tools is performed using only artificial,summative and ex-post strategies; 2. While usability evaluation is quite common, evaluationof enhanced privacy is lacking. This research hopes to contribute to better PET-tooldevelopment, and encourage the inclusion of users in the evaluation and design process.
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| 68. |
- Rizk, Aya, 1988-
(författare)
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Data-driven Innovation : An exploration of outcomes and processes within federated networks
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The emergence and pervasiveness of digital technologies are changing many aspects of our lives, including what and how we innovate. Industries and societies are competing to embrace this wave of digitalization by developing the right infrastructures and ecosystems for innovation. Similarly, innovation managers and entrepreneurs are using digital technologies to develop novel products, services, processes, business models, etc. One of the major consequences of digitalization is the massive amounts of machine-readable data generated through digital interactions. But this is not only a consequence, it is also a driver for other innovations to emerge. Employing analytical techniques on data to extract useful patterns and insights enables different aspects of innovation. During the last decade, scholars within digital innovation have started to explore this relationship between analytics and innovation, a phenomenon referred to as data-driven innovation (DDI). Most theories to date view analytics as variable that affects innovation in performative terms and treats it as a black-box. However, if the innovation managers and entrepreneurs are to manage and navigate DDI, and for the investors, funders and policymakers to take informed decisions, they need a better understanding of how DDI outcomes (i.e. market offerings such as products and services) are shaped and how they emerge from a process perspective.This dissertation explores this research gap by addressing two research questions: “What characterizes data-driven innovation outcomes?” and “How do data-driven innovations emerge in federated networks?” A federated network is a type of – increasingly common – contemporary innovation structure that is also enabled by digital technology. The dissertation is based on a compilation of five articles addressing these questions. The overall research approach follows a multiple case study design and the empirical investigation takes place in two case sites corresponding to two EU-funded projects.As a result, a classification taxonomy is developed for data-driven digital services. This taxonomy contributes to the conceptualization of DDI outcomes grounded on static and dynamic characteristics. In addition, a DDI process framework is proposed that highlights the importance of exploration, the temporal relationship between data acquisition and innovation development, and the various factors that influence the process along with examples of their contextual manifestations. Finally, social and cognitive interactions within federated networks of DDI are explored to reveal that the innovation teams rely on data-driven representations to facilitate various stakeholders’ engagement and contribution throughout the process. These representations eventually stabilize into boundary objects that retain the factual integrity of the data and analytical models but are also flexible for contextual interpretation and use. These findings contribute to the current discourse within digital innovation by introducing the lens of data analytics to conceptualize a specific type of digital artifacts, and well as providing a rich descriptive account of an extended digital innovation process. They also contribute to the discourse on data-driven innovation by providing an empirical account of DDI from a process viewpoint.
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| 69. |
- Rizk, Aya, 1988-, et al.
(författare)
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Data-driven innovation processes within federated networks
- 2022
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Ingår i: European Journal of Innovation Management. - : Emerald Group Publishing Limited. - 1460-1060 .- 1758-7115. ; 25:6, s. 498-526
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Tidskriftsartikel (refereegranskat)abstract
- PurposeWithin digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. Accordingly, there is a growing domain for studying data-driven innovation (DDI), especially in contemporary contexts of innovation networks. The purpose of this study is to explore how DDI processes take form in a specific type of innovation networks, namely federated networks.Design/methodology/approachA multiple case study design is applied in this paper. We draw our analysis from data collected over six months from four cases of DDI. The within-analysis is aimed at constructing the DDI process instance in each case, while the crosscase analysis focuses on pattern matching and cross-case synthesis of common and unique characteristics in the constructed processes.FindingsEvidence from the crosscase analysis suggests that the widely accepted four-phase digital innovation process (including discovery, development, diffusion and post-diffusion) does not account for the explorative nature of data analytics and DDI. We propose an extended process comprising an explicit exploration phase before development, where refinement of the innovation concept and exploring social relationships are essential. Our analysis also suggests two modes of DDI: (1) asynchronous, i.e. data acquired before development and (2) synchronous, i.e. data acquired after (or during) development. We discuss the implications of these modes on the DDI process and the participants in the innovation network.Originality/valueThe paper proposes an extended version of the digital innovation process that is more specifically suited for DDI. We also provide an early explanation to the variation in DDI process complexities by highlighting the different modes of DDI processes. To the best of our knowledge, this is the first empirical investigation of DDI following the process from early stages of discovery till postdiffusion.
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| 70. |
- Rizzo, Agatino, et al.
(författare)
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Transformative thinking and urban living labs in planning practice : a critical review and ongoing case studies in Europe
- 2021
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Ingår i: European Planning Studies. - : Taylor & Francis. - 0965-4313 .- 1469-5944. ; 29:10, s. 1739-1757
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Forskningsöversikt (refereegranskat)abstract
- The aim of this article is to critically situate co-production methods such as that of the urban living lab within contemporary planning theory and in particular to the ideas of ‘agonistic planning’ and the ‘trading zone’. By critically review relevant literature and discussing the results of an ongoing interdisciplinary project, we will show a number of potentials and issues when translating the urban living lab idea to planning contexts. Potentially our urban living labs have opened up opportunities for local planners to discuss controversial issues by using the idea of nature based solution as a boundary-object/trading-zone. On the other hand, planners’ positivistic and incremental understanding of city making hinders a transformative understanding of the urban living lab and nature based solution in favour of more fashionable technological fixes.
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