Big Data and Data Analytics for Enhanced Decision-Making in the Public Sector

Big Data and Data Analytics (BDA) has the potential to enhance the government sector by providing a better understanding of current challenges, external environment, and citizens\u27 needs to assist with effective design and implementation of policies and services. Although BDA can bring enormous benefits, organisations are finding it challenging to realise the true potential of data. The focus of the paper is on studying the effect of organisational maturity in effective application of BDA in the public sector. Drawing from theories of policymaking and information systems, the study treats BDA as a complex phenomenon from the social-technical perspective. The contribution of this study is to provide an initial understanding of how BDA can be applied more effectively to enhance decision-making across a range of public sector areas

Open innovation, value creation and value capture : an introduction

To be successful in open innovation, firms need to craft an effective strategy for both value creation and value capture. However, these two aspects are difficult to combine, and there are important tensions that deserve closer examination. The aim of this special section is to offer original perspectives on key conceptual and empirical research questions related to how open innovation can help organizations to create and capture value, the extent to which there might be a tension between value creation and value capture in open innovation strategies, and how this tension can be effectively dealt wit

What is paradox in Information Systems research? Towards a narratology

Paradoxes are intriguing narrative devices, enabling information systems (IS) researchers to develop captivating stories that encapsulate the richness of the emergent socio-technical phenomena they study. However, existing paradox research in IS has been fragmented by incoherency around the meaning of the term ‘paradox’. To help provide greater consistency and clarity, this paper works towards a narratology of paradox in IS. We review the existing IS paradox literature as captured in a sample of 139 publications in IS and related journals. In the first round of analysis, we identify six archetypes of how authors engage with paradoxes: complication, resolution, adaptation, problematisation, explanation, and exaptation. In the second round of analysis, we inductively code the different patterns in which narratives about paradoxes unfold in the existing IS paradox literature. Our framework, when completed, can help aspiring authors of IS paradox papers more clearly articulate their contribution

Structuring the Jungle of Capabilities Fostering Digital Innovation

Driven by digitalization, the business environment is changing at an increasing pace. To be able to react to this, organizations must gain competitive advantages through Digital Innovation (DI). This special form of innovation requires a reorganization and further development of the resource and capability base of an organization. The existing literature shows a proliferation of definitions and a jungle of individual capabilities with regard to DI. Based on a structured literature review and a qualitative analysis of existing capabilities, the paper presents a DI Capability Model. By structuring layers, areas and associated capabilities, the model provides the first holistic view in the literature. It will serve as a basis for a targeted scientific discourse and a valuable orientation model for the development of a capability composition to foster DI in organizations.</p

Acute

This project digs deep into issues of accessibility, education, and transparency for those who create health data. By using surveys, interviews, user testing, and secondary research, this project aims to both provide a possible solution while also underlining the market resistance to a more equal exchange between consumer and producer. Data collection is a part of everyone’s lives. Privacy is a hot topic. Many people misunderstand data use, and it seems corporations are taking advantage of that. Our bodies and our devices produce and create data, and that information is then used for research, profit, or general consumer benefit. This is just as true when it comes to medical data. Though it is protected information, patients do not know how it gets used, who uses it, and do not have comprehensive access. Legally, we should have access to our medical records, yet there is no way to view information in a comprehensive way in one place. It gets harder and harder to remember years of medical history for yourself, let alone family history, some of which may be crucial to diagnosis. Some patients have been charged for unknown bills, with no way to track down the entity that ordered those costly tests. There is currently no way to see if and how data from wearable technology is adopted into health records. The lack of comprehensive record availability to view patient histories and the lack of accessibility to programs like wearable technology highlight the limitations of electronic health records (EHR) and hospital systems that silo information

Artificial Intelligence, CEO Turnover, and Directional Change in Firm Innovation

We examine the role of artificial intelligence (AI) in facilitating a change in innovation directions after a leadership change. Using patent data for firms that have gone through a CEO turnover, we find that firms with greater AI investment are more successful in changing their innovation directions. The effect of AI is driven principally by the continued development of innovation in areas that are modestly different from the past. Further analyses show that this effect is likely due to firms with AI investment that can enable strategic change in cultivating culture of exploring frontiers in innovation and managing R&D. A new CEO can direct more resources to the acquisition of employees with greater technological capabilities such as AI skills to facilitate the innovation change. Overall, our study sheds light on the value of AI in fostering the change in innovation directions during uncertain and turbulent times

Measuring Firm Innovation and its Relationship with IPO and M&A Activities

This paper examines the changes in firms’ innovation performance around initial public offerings (IPO) and mergers and acquisitions (M&A) using innovation data based on patent applications, new product introductions, and scientific article publications. The quantity of innovation is measured by number of innovative outputs and the quality of innovation is measured by a variety of metrics including patent or article citation count and content-based novelty score. Results generally show that innovation quantity increases while innovation quality declines following IPO and M&A events. The findings are consistent among patent-based, product-based, and publication-based metrics, and confirm with the results from previous literature. In addition, innovation performance is found to vary with financial performance and industry characteristics. Firms that exhibit larger asset and cash holdings, higher profitability, and more R&D investments are in general more innovative in terms of both quality and quantity. In post-IPO or post-M&A years, higher industry sales concentration and geographic concentration tend to correlate with lower innovation quantity and higher innovation quality. This paper also attempts to study the mobility of innovative employees around IPO and M&A, but the results lack sufficient insights on whether the observed post-event decline in innovation quality can be explained by changes in the composition of innovators. Overall, despite the ability to produce more innovations after going public or acquiring another company, firms should be mindful of the potential loss in innovation quality

Data in design: How big data and thick data inform design thinking projects

Scholars and practitioners have recognized that making innovation happen today requires renewed approaches focused on agility, dynamicity, and other organizational capabilities that enable firms to cope with uncertainty and complexity. In turn, the literature has shown that design thinking is a useful methodology to cope with ill-defined and wicked problems. In this study, we address the question of the little-known role of different types of data in innovation projects characterized by ill-defined problems requiring creativity to be solved. Rooted in qualitative observation (thick data) and quantitative analyses (big data), we investigate the role of data in eight design thinking projects dealing with ill-defined and wicked problems. Our findings highlight the practical and theoretical implications of eight practices that differently make use of big and thick data, informing academics and practitioners on how different types of data are utilized in design thinking projects and the related principles and practices

Leveraging Data Management Capabilities for Innovation Capabilities: The Moderating Role of Cross-Functional Integration

In today’s dynamic and competitive business environment, data are crucial for sustaining a competitive advantage. Organizations are also constantly seeking ways to enhance their innovation capabilities in order to stay ahead of the competition. One critical factor that has been identified as influential in enabling innovation are the organization’s data management capabilities. Past studies have found that cross-functional integration may enhance the impact of data management on innovation. Hence, this study aimed to investigate the influence of data management capabilities on explorative and exploitative innovation by considering the role of cross-functional integration as a moderating variable. This study used 116 data samples from medium and large companies across different industries in Indonesia. The PLS-SEM analysis was applied to test the research hypotheses. The results indicate that data management capabilities as a third-order construct, consisting of three dimensions, namely data governance, technology, and skills, have significant direct influences on explorative and exploitative innovation. This study demonstrated that cross-functional integration still plays an important role in amplifying the relationship between data management capabilities and innovation capabilities, especially in relation to explorative innovation

Advanced Technologies and Worker Voice

The interplay between labour institutions and firm-level adoption of new technologies such as robotics andother advanced digital tools remains poorly understood. Using a cross-sectional sample of more than 20,000European establishments, we document a positive association between shop-floor employee representation (ER)and utilization of emerging technologies. We explore mechanisms driving this correlation by exploiting richinformation on the role played by ER in relation to well-defined decision areas of management, such as workorganization, dismissals, training and working time. In addition, we conduct a quantitative case study usinga panel of Italian firms and exploiting size-contingent policy rules governing the operation of ER bodies inthe context of a local-randomization regression discontinuity design. The analysis suggests a positive effectof ER on investments in advanced technologies around the firm size cut-off, although results are sensitiveto type of technology and specification choices. We also document positive effects on training and processinnovation, and no evidence of changes in composition of employment. Our findings cast doubt on the ideathat ER discourages technology adoption. Rather, ER seems to influence workplace practices that enhance thecomplementarity between labour and new advanced technologies