Peter John’s latest book, How Far to Nudge?: Assessing Behavioural Public Policy, is part intellectual history, part a tale of policy diffusion, and part a personal reflection on the behavioral science revolution in public policy and administration by someone who himself was one of its key rebels. John, who is a professor of political science and public policy in the United Kingdom, was an early protagonist and practitioner of behavioral and experimental approaches to public administration. In a sense, this book completes a trilogy of volumes by him on the topic: the first, Nudge, Nudge, Think, Think: Experimenting with Ways to Change Civic Behavior (John et al. 2011), documents cases in which John and his collaborators used behavioral insights (such as the tendency to comply with social norms) to test nudge strategies aimed at influencing citizens to recycle, volunteer, vote, and give to charity; in the second, Field Experiments in Political Science and Public Policy (John 2017), John provides guidance on the design and implementation of randomized controlled trials of behavioral interventions involving government programs and services. In How Far to Nudge?, John steps back to reflect more broadly on the origins, practices, limitations, ethics, and political implications of behavioral public policy. As he writes in the introduction: “Given the success of nudge, now is the time to broaden it out and to link it more closely to democratic practice” (p. 14). He begins by making the case that many important social, health, and economic challenges facing government have their roots in both individual and collective human behaviors. Diseases are often determined by health behaviors, for example, although John is quick to point out the structural influences (such as poverty and access to health care) that play a key role in addition to human behavior. Still, he makes a compelling argument for the important role of behavior change in many areas of public policy and administration. Next, he tells the fascinating story of the behavioral revolution in the social sciences. For those already acquainted with popular books such as Daniel Kahneman’s Thinking, Fast and Slow (Kahneman and Egan 2011), Richard Thaler’s Misbehaving (Thaler and Ganser 2015), and Michael Lewis’ The Undoing Project (Lewis 2016), this story will be somewhat familiar. But John tells it from his own perspective as a political scientist and articulates the connections to public policy and administration. Amusingly, he enjoys cluing his reader in on some of the hype and self-promotion that accounts, at least in part, for the popularity of behavioral economics in the halls of government and in the public imagination. But he pays due respect as well to the important advances and insights of the likes of Kahneman, Amos Tversky, Thaler, Cass Suntein, Daniel Ariely, and others whose work over the years formed the intellectual foundations for behavioral public policy. The middle chapters of the book reflect on the practices and limitations of behavioral policy in government, a narrative informed to a large extent by John’s own extensive work in the United Kingdom and other countries applying nudge strategies to government. He discusses how nudge units were established in government agencies in the United Kingdom (especially the Behavioral Insights Team) and elsewhere and, importantly, how their continuation often depends on the contingencies of political leadership and changing priorities. Usefully, John specifies some of the key (and often unmentioned) limitations of behavioral insights in government, such as the limited range of application (mostly letters, forms, and messages), small and often temporary effects, limited generalizability, and the worry that a focus on nudge diverts the government’s attention from pursuing more substantive (and expensive) solutions to pressing social and policy problems. John also devotes a chapter to the ethics of nudging, which has been defined largely as a form of libertarian paternalism because it entails both choice and direction (nudge). John fully recognizes the dangers inherent in the creation of a “psychological state” but remains optimistic about the potential of nudging, given the generally limited and transparent nature of the nudge initiatives to date and the potential to incorporate nudge tactics into reflective, self-governance practices. Usefully, John also reminds us that public policy-making, in general, involves difficult ethical questions and that nudge is often a less intrusive instrument than laws, regulations, and other conventional instruments of government control over people’s behavior. In the last chapters, as foreshowed throughout the book, John make an original argument: nudges work well enough, but they must be made more open, democratic, and deliberative to truly sustain long-term behavior change and thus improve government and society. “Nudge plus (think)” is what he advocates. This approach envisions a behavioral public policy that leverages both System 1 (fast, intuitive) and System 2 (slow, deliberate) thinking, following Kahneman’s well-known formulation, in the service of better outcomes for individuals and society (Kahneman and Egan 2011). Thus, John highlights ways in which nudge initiatives can incorporate citizen participation and can be made more transparent and explained more fully to citizens. In addition, he makes the point that nudge should not be just a tool of technocrats but should be decentralized to agencies, local governments, and civil society organizations to incorporate behavioral insights into their own autonomous activities. John explains: “The idea is that a combination of nudging and thinking can help the creation of an automated and self-regulating system whereby people get to their goals and where there is a synergy between social and individual aims” (p. 133). But, of course, this formulation is complicated by the implications of the very behavioral revolution John writes about. If we believe what modern psychology has to say about the large role in human behavior played by automatic thought processes (thinking fast), emotions (gut feelings), and our limited capacity for rational problem solving (bounded rationality), then conscious deliberation only gets us so far. The conscious mind is the tip of an iceberg, we have come to discover, consisting of a murky mass of evolutionary or deeply learned associations, construals, heuristics, and biases. But what John argues in his book, it seems to me, is that this conscious tip of the iceberg can nevertheless reflect on how it deals with and attempts to influence the unconscious mass of forces active below the surface. Just like a patient in psychotherapy learns to recognize and deal with the deeply buried emotions that intrude on his life, even if he cannot alter them, so too a democratic society can learn to recognize its cognitive biases and behavioral bugs and find ways, through democratic deliberation, to deal with them and thus live a better collective life. In sum, Peter John’s How Far to Nudge? provides a thoughtful, insightful and original take on the behavioral science revolution in public policy and administration. The book serves as a helpful resource for those looking for an overview of the current status of nudge in government, and it would provide a useful text for graduate courses that include a focus on behavioral public policy and administration. And yet the book is thought-provoking for those already familiar with the topic as well because, having worked extensively at applying nudge tactics in government and having read widely in the behavioral sciences, John is able to provide a uniquely informed perspective on the practices, limitations, ethics, and political implications of the behavioral turn in public policy and public administration as this approach assumes an increasingly prominent role in governments around the world.
Social Representations and Identity
Academic and Historical Perspectives in Psychology
Blockchain-based platforms are emerging to provide solutions for technical and governance challenges associated with genomic data sharing. Providing capabilities for distributed data stewardship and participatory access control along with effective ways for enforcement of the data access agreements and data ownership are among the major promises of these platforms.
Tomás Robles, Borja Bordel, Ramón Alcarria, Diego Sánchez-de-Rivera
Blockchain enables the creation of distributed ledgers as a type of database that is shared, replicated, and synchronized among the members of a network. In this paper we analyze how distributed ledgers can be used for empowering end-users to self-manage their own data, enabling third parties to access those data under a cryptographic management model. We propose a use case where both blockchain and smart contracts are employed by using cryptographic technology to enable user empowerment of data management in AmI. Finally, we analyze strengths and weaknesses of the proposed scenario.
Interest in cryptocurrencies has skyrocketed since their introduction a decade ago, with hundreds of billions of dollars now invested across a landscape of thousands of different cryptocurrencies. While there is significant diversity, there is also a significant number of scams as people seek to exploit the current popularity. In this paper, we seek to identify the extent of innovation in the cryptocurrency landscape using the open-source repositories associated with each one. Among other findings, we observe that while many cryptocurrencies are largely unchanged copies of Bitcoin, the use of Ethereum as a platform has enabled the deployment of cryptocurrencies with more diverse functionalities.
Cryptocurrency has been a trending topic over the past decade, pooling tremendous technological power and attracting investments valued over trillions of dollars on a global scale. The cryptocurrency technology and its network have been endowed with many superior features due to its unique architecture, which also determined its worldwide efficiency, applicability and data intensive characteristics. This paper introduces and summarises the interactions between two significant concepts in the digitalized world, i.e., cryptocurrency and Big Data. Both subjects are at the forefront of technological research, and this paper focuses on their convergence and comprehensively reviews the very recent applications and developments after 2016. Accordingly, we aim to present a systematic review of the interactions between Big Data and cryptocurrency and serve as the one stop reference directory for researchers with regard to identifying research gaps and directing future explorations.
<em>The research paper deals</em><em> with Bitcoin ,its mining and how mining actually works how Bitcoins are made, uses of Bitcoin why we should use Bitco in. Digital wallets for storing Bitcoins It also covers some of the biggest issues associated with Bitcoin like adecentralized currency covering the vast problem of Doublespending ininitial days of Bitcoin trading.The uses of Block-chain in Bit coin’stransaction to solve the problem of Double spending of Bitcoin.Applications of Block-chain other than crypto currency like in healthcare sector,reale state, voting, cyber security,it also covers sections by which we can make block-chain faster especially while buying crypto currencies and why SSDs should be preferred for Bloch-chain operations.</em>
This paper documents inequitable transit-based accessibility to sectoral jobs among population groups with different educational attainment and hukou status in Beijing, China. A cumulative transit-based job accessibility measure is applied and multiple data sources are used, including the transit travel-time data from a Chinese web mapping service and the population and employment distribution data from the 2010 Population Census and the 2013 Economic Census of Beijing. We find clear differences in transit-based job accessibility among employment sectors and among population groups in Beijing. On average, jobs in the finance sector are the most accessible by transit, and jobs in the manufacturing sector are the least accessible by transit. Despite having the highest transit dependency, the low-educated migrant population has the lowest transit-based job accessibility regardless of employment sectors. The disparities are especially large when tying specific populations with specific sectors. Within 60 minutes, the low-educated migrant population using transit, on average, can only access 4.6% of total manufacturing jobs in Beijing. In contrast, the same measure for the highly educated local population accessing jobs in the finance sector is as high as 48.3%. The findings suggest that general transit improvements and jobs and population redistribution efforts, without specific sectoral and population considerations, are unlikely to create equal access to job opportunities. In Beijing, greater attention must be paid to connect the low-educated migrant population to low-skilled and decentralized jobs in the manufacturing, construction, and transportation and storage sectors.
Recently, changes within the business industry have led to human resource management (HRM) positions and structures being reconsidered. Human resources (HR) used to be centralized, but the constant changes to organizational culture has caused HR to become decentralized. The HR operations have been incorporated into other departments, as well. Now, HRM is essential to business processes that mirror other departments, such as accounting and finance, but HR is still centralized in specialized areas, such as recruitment and compensation. Examining Goldratt & Cox's “The Goal” reveals its involvement with HRM. This study evaluates the implication of HRM on a business, its relationship to the Theory of Constraints (TOC), and the ways in which these concepts can aid a business in reaching its main objective.
Blockchain and Tangle are data structures used to create an immutable public record of data insured by a network of peer-to-peer participants who maintain a set of constantly growing data records known as ledgers. Blockchain and Tangle technologies are a decentralized solution that guarantees the exchange of large amounts of trusted messages, among billions of connected IoT devices, which are very valuable as they are valid and complete. This highly encrypted and secure peer-to-peer messaging mechanism is adopted in this project to manage the processing of IoT transactions and the coordination between the devices that interact with the process. To maintain private transactions, secure and trustless, the distributed consensus algorithms are responsible for validating and choosing transactions and recording them in the global ledger. The results showed that the speed of the consensus algorithms can affect the creation in real time of reliable stories that track the events of the IoT networks. After incorporating Complex Event Processing that allows selecting only those high level events, it is possible to get an improvement in many situations. The result is a Middleware system that provides a framework for the construction of large-scale computer applications that use Complex Events Processing and different decentralized ledgers such as the blockchain of Ethereum or IOTA Tangle, for secure data storage.
Transaction throughput, confirmation latency and confirmation reliability are fundamental performance measures of any blockchain system in addition to its security. In a decentralized setting, these measures are limited by two underlying physical network attributes: communication capacity and speed-of-light propagation delay. Existing systems operate far away from these physical limits. In this work we introduce Prism, a new proof-of-work blockchain protocol, which can achieve 1) security against up to 50% adversarial hashing power; 2) optimal throughput up to the capacity C of the network; 3) confirmation latency for honest transactions proportional to the propagation delay D, with confirmation error probability exponentially small in CD ; 4) eventual total ordering of all transactions. Our approach to the design of this protocol is based on deconstructing the blockchain into its basic functionalities and systematically scaling up these functionalities to approach their physical limits.
Michael Alexeev, Nikolay Avxentyev, Arseny Mamedov, Sergey Sinelnikov-Murylev
Using a panel of Russian regions, we estimate the link between intraregional fiscal decentralization and regional budget deficits. Although Russia’s regions are not as autonomous (either politically or fiscally) as regions in some other federal states, we obtain robust and statistically and economically significant results. Specifically, expenditure decentralization has a positive effect on consolidated regional budget balances, while transfer dependence of municipalities is associated with higher deficits. The impact of revenue decentralization depends on whether a regional government can use its tax revenue assignments with the same high degree of discretion that generally characterizes explicit fiscal transfers. We show that a 2009 local finance reform that limited the discretion of regional governments to assign regional tax revenue to municipalities has changed the effect of tax decentralization on budget discipline.
Oct 17, 2018·Radziwill, Nicole M. (2018, October). Let's Get Digital: The many ways the fourth industrial revolution is reshaping the way we think about quality. Quality Progress, ASQ, p. 24-29
The technology landscape is richer and more promising than ever before. In many ways, cloud computing, big data, virtual reality (VR), augmented reality (AR), blockchain, additive manufacturing, artificial intelligence (AI), machine learning (ML), Internet Protocol Version 6 (IPv6), cyber-physical systems and the Internet of Things (IoT) all represent new frontiers. These technologies can help improve product and service quality, and organizational performance. In many regions, the internet is now as ubiquitous as electricity. Components are relatively cheap. A robust ecosystem of open-source software libraries means that engineers can solve problems 100 times faster than just two decades ago. This digital transformation is leading us toward connected intelligent automation: smart, hyperconnected agents deployed in environments where humans and machines cooperate, and leverage data, to achieve shared goals. This is not the worlds first industrial revolution. In fact, it is its fourth, and the disruptive changes it will bring suggest we will need a fresh perspective on quality to adapt to it.
We propose a novel sidechain construction tailored to be compatible with the Horizen blockchain and designed for conducting secure and decentralized cross-chain transfers without requiring the mainchain nodes to track sidechains to verify them. The proposed scheme can also be adopted for other similar blockchain systems. We show that our cross-ledger transfer mechanism is secure under certain plausible assumptions.
Payment networks, also known as channels, are a most promising solution to the throughput problem of cryptocurrencies. In this paper we study the design of capital-efficient payment networks, offline as well as online variants. We want to know how to compute an efficient payment network topology, how capital should be assigned to the individual edges, and how to decide which transactions to accept. Towards this end, we present a flurry of interesting results, basic but generally applicable insights on the one hand, and hardness results and approximation algorithms on the other hand.
Georgia Avarikioti, Gerrit Janssen, Yuyi Wang, Roger Wattenhofer
Payment channels are the most prominent solution to the blockchain scalability problem. We introduce the problem of network design with fees for payment channels from the perspective of a Payment Service Provider (PSP). Given a set of transactions, we examine the optimal graph structure and fee assignment to maximize the PSP's profit. A customer prefers to route transactions through the PSP's network if the cheapest path from sender to receiver is financially interesting, i.e., if the path costs less than the blockchain fee. When the graph structure is a tree, and the PSP facilitates all transactions, the problem can be formulated as a linear program. For a path graph, we present a polynomial time algorithm to assign optimal fees. We also show that the star network, where the center is an additional node acting as an intermediary, is a near-optimal solution to the network design problem.