Big data and dynamic capabilities in the digital revolution: The hidden role of source variety

Recent research frames big data as a resource enhancing dynamic capabilities through improved prediction, decision-making, and data-driven innovation. In contrast, this study frames big data as an evolutionary driver that channels firms' knowledge and attention in specific directions, implying that firms need multiple big data sources to be receptive and dynamically capable. I apply this framework to the context of the digital revolution and focus on the impact of big data on firms' digitalization priorities. By leveraging a large-scale survey of more than twenty thousand Italian firms of all sizes, I find that big data improves the digitalization awareness of firms only if they gather big data from more than one source (otherwise, counterintuitively, it may even decrease it). I also find a positive effect of source variety both on the likelihood of prioritizing individual digitalization factors and on the variety of digitalization factors prioritized. Such effects appear to be stronger for small firms relative to their larger counterparts. Given the path dependence of digitalization trajectories, these findings have relevant policy implications in the context of initiatives like the European strategy for data and the SME strategy for a sustainable and digital Europe.     

Big data management in healthcare: Adoption challenges and implications

The computerized healthcare information system has undergone tremendous advancements in the previous two decades. Medical institutions are paying further attention to the replacement of traditional approaches that can no longer handle the increasing amount of patient data. In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care. This research aims to evaluate organization-driven barriers in implementing a healthcare information system based on big data. It adopts the analytic network process approach to determine the aspect weight and applies VlseKriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) to conclude a highly appropriate strategy for overcoming such barriers. The proposed model can provide hospital managers with forecasts and implications that facilitate the withdrawal of organizational barriers when adopting the healthcare information system based on big data into their healthcare service system. Results can provide benefits for increasing the effectiveness and quality of the healthcare information system based on big data in the healthcare industry. Therefore, by understanding the sequence of the importance of resistance factors, managers can formulate efficient strategies to solve problems with appropriate priorities.     

Big data adoption: State of the art and research challenges

Big data adoption is a process through which businesses find innovative ways to enhance productivity and predict risk to satisfy customers need more efficiently. Despite the increase in demand and importance of big data adoption, there is still a lack of comprehensive review and classification of the existing studies in this area. This research aims to gain a comprehensive understanding of the current state-of-the-art by highlighting theoretical models, the influence factors, and the research challenges of big data adoption. By adopting a systematic selection process, twenty studies were identified in the domain of big data adoption and were reviewed in order to extract relevant information that answers a set of research questions. According to the findings, Technology–Organization–Environment and Diffusion of Innovations are the most popular theoretical models used for big data adoption in various domains. This research also revealed forty-two factors in technology, organization, environment, and innovation that have a significant influence on big data adoption. Finally, challenges found in the current research about big data adoption are represented, and future research directions are recommended. This study is helpful for researchers and stakeholders to take initiatives that will alleviate the challenges and facilitate big data adoption in various fields.     

Big data analytics adoption: Determinants and performances among small to medium-sized enterprises

Big data analytics (BDA) adoption is a game-changer in the current industrial environment for precision decision-making and optimal performance. Nonetheless, the determinants or consequences of its adoption in small and medium enterprises remain unclear, hence the objective of this study. Data analysis of 171 Iranian small and medium manufacturing firms revealed that complexity, uncertainty and insecurity, trialability, observability, top management support, organizational readiness, and external support affect significantly on BDA adoption. The findings confirm the strong impact of BDA adoption in small to medium-sized enterprises, marketing and financial, performance enhancement. Understanding the drivers of BDA adoption helps managers to employ appropriate initiatives that are vital for effective implementation. The results enable BDA service providers to attract and diffuse BDA in small to medium-sized enterprises.     

Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes

We introduce Big Data Analytics (BDA) and Sentiment Analysis (SA) to the study of international negotiations, through an application to the case of the UK-EU Brexit negotiations and the use of Twitter user sentiment. We show that SA of tweets has potential as a real-time barometer of public sentiment towards negotiating outcomes to inform government decision-making. Despite the increasing need for information on collective preferences regarding possible negotiating outcomes, negotiators have been slow to capitalise on BDA. Through SA on a corpus of 13,018,367 tweets on defined Brexit hashtags, we illustrate how SA can provide a platform for decision-makers engaged in international negotiations to grasp collective preferences. We show that BDA and SA can enhance decision-making and strategy in public policy and negotiation contexts of the magnitude of Brexit. Our findings indicate that the preferred or least preferred Brexit outcomes could have been inferred by the emotions expressed by Twitter users. We argue that BDA can be a mechanism to map the different options available to decision-makers and bring insights to and inform their decision-making. Our work, thereby, proposes SA as part of the international negotiation toolbox to remedy for the existing informational gap between decision makers and citizens’ preferred outcomes.     

Big data analytics in health sector: Theoretical framework,techniques and prospects

Clinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research.     

Leveraging digital forensics and data exploration to understand the creative work of a filmmaker: A case study of Stephen Dwoskin's digital archive

This paper aims to establish digital forensics and data exploration as a methodology for supporting archival practice and research into a filmmaker's creative processes. We approach this by exploring the digital legacy hard drives of the late artist Stephen Dwoskin (1939–2012), who is recognised as an influential filmmaker at the forefront of the shift from analogue to digital film production. The research findings of this case study show that digital forensics is effective in extracting a timeline of hard drive activities, data that can be explored to reveal clues about the artist's personal/professional history, stages of creative processes, and technical environment. The paper further demonstrates how this is related to current thinking around user-centred archival workflow and understanding of creative processes. The broader impact of the work for advancing digital archiving and research into creative processes is highlighted, concluding with a discussion of how, going forward, the approach can be coupled with deeper content analysis to reveal what influences editing choices taking place over time.     

Spatial information and the legibility of urban form: Big data in urban morphology

Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, conceptualize proposed designs, compare alternatives, and engage the public. Classic urban form visualizations – from Giambattista Nolli’s ichnographic maps of Rome to Allan Jacobs’s figure-ground diagrams of city streets – have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives.     

学科领域期刊科研数据发表政策剖析——以美国化学学会期刊为例

【目的】剖析化学学科领域科学期刊的数据发表政策,了解期刊数据政策的现状。【方法】 以ACS期刊为例,以期刊投稿指南为数据源,梳理和比较分析ACS期刊对发表论文的数据内容、数据格式、数据共享的要求。【结果】ACS的47种期刊要求论文作者将数据作为支撑信息提交,对于包含序列数据、结构数据、电子显微镜数据、微阵列数据、转基因生物和突变体五类特定类型数据的论文要求将该数据存储到推荐的数据仓储中,涉及五类数据的期刊总共有20种。【结论】可作为化学领域科研人员在ACS上发表论文的参考依据,为国内学术期刊数据政策的实施提供借鉴。     

Big data as governmentality in international development: Digital traces,algorithms, and altered visibilities

Statistics have long shaped the field of visibility for the governance of development projects. The introduction of big data has altered the field of visibility. Employing Dean's “analytics of government” framework, we analyze two cases—malaria tracking in Kenya and monitoring of food prices in Indonesia. Our analysis shows that big data introduces a bias toward particular types of visualizations. What problems are being made visible through big data depends to some degree on how the underlying data is visualized and who is captured in the visualizations. It is also influenced by technical factors such as distance between mobile phone towers and the truth claims that gain legitimacy.     

The basis for bibliomining: Frameworks for bringing together usage-based data mining and bibliometrics through data warehousing in digital library services

Over the past few years, data mining has moved from corporations to other organizations. This paper looks at the integration of data mining in digital library services. First, bibliomining, or the combination of bibliometrics and data mining techniques to understand library services, is defined and the concept explored. Second, the conceptual frameworks for bibliomining from the viewpoint of the library decision-maker and the library researcher are presented and compared. Finally, a research agenda to resolve many of the common bibliomining issues and to move the field forward in a mindful manner is developed. The result is not only a roadmap for understanding the integration of data mining in digital library services, but also a template for other cross-discipline data mining researchers to follow for systematic exploration in their own subject domains.     

数字创新生态系统：理论构建与未来研究

数字化重塑了创新主体之间的价值共创方式,拓展了现有创新生态系统理论,引发关于数字创新生态系统的思考。本文提出数字创新生态系统的两种表现形式：创新导向的数字生态系统（又称“数字创新生态系统Ⅰ型”）以及数字赋能的创新生态系统（又称“数字创新生态系统Ⅱ型”）。创新导向型的数字生态系统旨在促进数字创新的产生、应用与扩散,这一围绕数字主体而形成的创新生态系统延续了数字生态系统收敛性、可扩展性、自生长性和模块性的基本特征。数字赋能的创新生态系统是数字化进程与创新主体间价值共创行为深度融合的结果,实现了创新生态系统内主体、结构、制度、功能和演进的数字化转型。数字创新生态系统Ⅰ型与Ⅱ型彼此渗透、相互促进,改进了创新主体之间的价值共创方式,推动了创新能力与创新效能的全面提升。最后,建议未来研究从案例分析、形成机制分析、发展战略分析、政策研究和监测研究等方面来健全和完善数字创新生态系统理论。     

Sitting on the Fence: Integrating the two worlds of scientific discovery and invention within the firm

Applying a within-firm perspective to the topic of the division of innovative labor, I explore the organization of scientific discovery at the firm level — specialized or integrated with invention. Using data on inventors and authors related to U.S. publicly-traded science-performing firms for the period 1980–2015, the paper deepens our understanding of the determinants and the tradeoffs associated with the strategic choice of scientific discovery organization. I show that integration is related to a tradeoff between short-term applied R&D and long-term fundamental R&D; while integration is beneficial for invention, it has adverse effects on its scientific output, which decrease invention in the long run. The negative relationship between integration and publication reduces the direct increase in patents due to integration by approximately 90%. To better understand firms’ R&D organizational choice, I present internal and external factors that have implications on the benefits and costs associated with integration: reliance on science, stage of technology, external market for technology, and R&D spillins. Finally, I present consistent implications in terms of market value and show that value creation is related to organizational structure.     

Stochastic identification and digital control of a heat exchanger: a simulation test case

In this paper, an extended simulation study is presented by which the power of modern digital identification and control methodology is tested against the nontrivial dynamics of a relatively simple yet nonelementary plant. Many critical issues which may significantly affect the success of the entire design process can be discussed along the lines of this study. The plant considered here is a liquid-saturated steam heat exchanger, where the liquid flow-rate is manipulated to regulate the outlet liquid temperature. All the numerical experiments have been conducted by digital simulation of a fairly standard nonlinear distributed parameter model.     

Crowd-based feedback and early-stage entrepreneurial performance: Evidence from a digital platform

The ability to identify early-stage venture potential, which has traditionally relied on experts, is challenging because new ideas are uncertain. However, judgment from a large number of evaluators can effectively identify promising ventures. This paper empirically studies whether crowd-based information generates informative feedback for entrepreneurs and seed investors. Using data on 701 early-stage founders of new ventures examined by 2600 evaluators, I estimated the effects of crowd-based ratings on survival and securing seed funds. I find that the crowd rating was uncorrelated with subsequent financing events from seed investors but increased a venture's probability of continuation by 3.1 percentage points. This effect became stronger as the number of evaluators increased. This finding highlights that a judgment aggregation offers information for nascent venture founders.     

Digital transformation and European small and medium enterprises (SMEs): A comparative study using digital economy and society index data

Digital transformation is profoundly transforming SMEs' business activities, bringing about comparative advantages and associated risks. Previous studies on digital transformation and SMEs focus on technology adoption, innovation, new value creation, and dynamic capabilities. However, it is unclear how digital technology affects SMEs' specific business activities. We study SMEs' customer access, increasing competition, external funding or access to finance, rising input costs, skilled labor shortages, exogenous shocks, global crises, and regulatory issues. This study aims to fill the literature gap by exploring the impact of digital technology, using digital economy and society index (DESI) as proxies for the SME issues. We use DESI and SME data from a survey on European enterprises’ access to finance. We find that digital transformation strengthens SMEs' ability and flexibility to address main business issues. Furthermore, findings reveal that digitally transformed SMEs have fewer concerns about access to new and traditional customers, competition changes, access to finance, increasing input costs, external shocks, and regulatory changes. However, digital transformation also brings risks, such as the shortage of skilled labor and experienced managers and loss of inherent competitiveness. The novelty of our work lies in supplying quantitative knowledge on the link between digital transformation and European SMEs' critical business concerns. These findings substantially increase our understanding of the impact of digital change on European SMEs' business activities.     

Policies for science, technology and innovation: Translating rationales into regional policies in a multi-level setting

Departing from a number of theoretical perspectives from which rationales for science, technology and innovation (STI) policy can be extracted, this paper discusses three questions. First, what rationales for public intervention can be derived from different economic theories, including theories usually associated with spatial dynamics and territorial relationships? Second, what policy instruments or policy-mixes can be associated with the various rationales? Third, what do these theories and associated rationales tell us about the territorial level or levels at which STI policies can usefully be designed and implemented?     

Positions and rewards: The allocation of resources within a science-based entrepreneurial firm

We study the link between resource allocation and employee publication in the open science in a quantitative case study of one science-based, entrepreneurial firm. We bridge the literature on incentives with that on authority structures to argue that a positive relationship between rewards and productivity will be strongest for individuals in positions of scientific leadership within the firm. In a novel dataset, we find that prolific publishers receive greater year-end bonuses and are allocated additional direct reports, but this relationship only holds for individuals in scientific leadership roles. These results contribute to our understanding of resource allocation processes and reward structures in science-based firms.     

Inborn errors of metabolism: Review and data from a tertiary care center

Inherited metabolic disorders are a heterogeneous group of genetic conditions mostly occurring in childhood. They are individually rare but collectively numerous, causing substantial morbidity and mortality. We have retrospectively reviewed a total of eight hundred and sixty nine cases with different age groups that had been referred from several diagnostic centers and hospitals of India to the Department of Metabolism in Narayana Hrudayalaya, as cases suspected with inborn errors of metabolism. Advanced techniques applied were to diagnose the disorders of inborn errors of metabolism. Data analyzed indicates occurrence of several metabolic disorders in our population. The need to screen for an inborn error of metabolism arises out of the fact that most cases take to irreversible effects as time progress. Emphasis has to be laid on early detection and prompt management, which could help in alleviating symptoms and preventing complications and consequent incapacitation.