Risky business? Welfare state reforms and government support in Britain and Denmark

Are welfare state reforms electorally dangerous for governments? Political scientists have only recently begun to study this seemingly simple question, and existing work still suffers from two shortcomings. First, it has never tested the reform–vote link with data on actual legislative decisions for enough points in time to allow robust statistical tests. Secondly, it has failed to take into account the many expansionary reforms that have occurred in recent decades. Expansions often happen in the same years as cutbacks. By focusing only on cutbacks, estimates of the effects of reforms on government popularity become biased. This article addresses both shortcomings. The results show that voters punish governments for cutbacks, but also reward them for expansions, making so-called compensation, a viable blame-avoidance strategy. The study also finds that the size of punishments and rewards is roughly the same, suggesting that voters’ well-documented negativity bias does not directly translate into electoral behavior

Nanoparticle detection in an open-access silicon microcavity

We report on the detection of free nanoparticles in a micromachined, open-access Fabry-P\'erot microcavity. With a mirror separation of $130\,\mu$m, a radius of curvature of $1.3\,$mm, and a beam waist of $12\,\mu$m, the mode volume of our symmetric infrared cavity is smaller than $15\,$pL. The small beam waist, together with a finesse exceeding 34,000, enables the detection of nano-scale dielectric particles in high vacuum. This device allows monitoring of the motion of individual $150\,$nm radius silica nanospheres in real time. We observe strong coupling between the particles and the cavity field, a precondition for optomechanical control. We discuss the prospects for optical cooling and detection of dielectric particles smaller than $10\,$nm in radius and $1\times10^7\,$amu in mass.Comment: 4 pages, 3 figure

Durch Amadeus zu Mozart? Das Komponistenporträt als Schlüssel zum Werk im Musikunterricht am Beispiel eines biographischen Musikfilms

Innerhalb eines größeren Forschungsrahmens, der alternative Zugangsweisen zur Musik umfaßt, ging es bei der in diesem Beitrag vorgestellten Studie darum, Hinweise dafür zu erhalten, ob Schülerinnen und Schüler durch die Kenntnis der Biographie eines Komponisten Interesse an dessen Musik bekommen. (DIPF/Orig.

Modellierung und Analyse individuellen Konsumentenverhaltens mit probabilistischen Holonen

Der Schwerpunkt dieser Arbeit liegt in der Entwicklung eines agentenbasierten, probabilistischen Konsumentenverhaltensmodells zur Repräsentation und Analyse individuellen Kaufverhaltens. Das Modell dient zur Entscheidungsunterstützung im Handel und speziell im Customer Relationship Management (CRM). Als Modellgrundlage wird eine Klasse probabilistischer Agenten eingeführt, die sich zu Holonen zusammenschließen können und deren Wissensbasen erweiterte Bayes';sche Netze (Verhaltensnetze) sind. Mit Hilfe probabilistischer Holone werden Kundenagenten entwickelt, die einzelne reale Kundenmodellieren. Dazu werden kundenindividuelle Verhaltensmuster unter Berücksichtigung von Domänenwissen aus historischen Kundendaten extrahiert und als nichtlineare Abhängigkeiten zwischen Einflussfaktoren und artikelbezogenen Kundenreaktionen in Verhaltensnetzen repräsentiert. Ein Kundenagent ist dabei ein Holon aus mehreren so genannten Feature-Agenten, die jeweils einzelne Kundeneigenschaften repräsentieren, entsprechende Feature-Verhaltensnetze verwalten und durch Interaktion das Gesamtverhalten des Kunden bestimmen. Die Simulation des Verhaltens besteht aus der Ermittlung von Kundenreaktionen auf vorgegebene Einkaufsszenarien mit Hilfe quantifizierbarer probabilistischer Schlussfolgerungen. Kundenagenten können sich durch Holonisierung zu Kundengruppenagenten zusammenschließen, die unterschiedliche Aggregationen des Kaufverhaltens der Gruppenmitglieder repräsentieren. Zur Bestimmung gleichartiger Kunden werden auf Basis der Verhaltensnetze mehrere Ähnlichkeitsanalyseverfahren sowie verhaltensbezogene Ähnlichkeitsmaße zum Vergleich des dynamischen Kaufverhaltens entwickelt. Bestehende Klassifikations- und Clusteringverfahren werden anschließend so erweitert, dass sie neben klassischen Attributvektoren verhaltensnetzbasierte Repräsentationen als Vergleichsgrundlage verwenden können. Darüber hinaus werden Verfahren zur Zuordnung anonymer Kassenbons zu vorgegebenen Kundengruppen entwickelt, um Ergebnisse von Kundensimulationen auf die Gesamtheit der anonymen Kunden eines Unternehmens übertragen zu können. Nutzen und Qualität der entwickelten Modelle, Verfahren und Maße werden mit Hilfe einer umfangreichen Software-Implementierung anhand mehrerer Anwendungsbeispiele aus der Praxis demonstriert und in einigen Fallstudien evaluiert — basierend auf realen Daten eines deutschen Einzelhandelsunternehmens.The focus of this work is the development of an agent-based, probabilistic model for representing and analysing individual consumer behaviour. The model provides a basis for decision making in marketing and especially in customer relationship management (CRM). As foundation of the model, a class of probabilistic agents is introduced. These agents can be merged to holonic agents (holons) and have probabilistic knowledge bases adapted from Bayesian networks (behaviour networks). An individual customer is modelled as a customer agent which is a probabilistic holon consisting of several feature agents. A feature agent represents a particular property (feature) of the customer';s behaviour and encapsulates appropriate feature-related behaviour networks. The total behaviour of a customer agent is determined by interaction of its feature agents. Individual behaviour patterns of a customer are extracted from real data — in consideration of given domain knowledge — and are represented within behaviour networks as non-linear dependencies between influencing factors and the customer';s product-related reactions. Behaviour simulation is realised by evaluation of expected reactions of customers on given shopping scenarios based on quantifiable, probabilistic reasoning. Customer agents are able to join to customer group agents which represent different behaviour aggregations of their members. Based on behaviour networks, several behaviour-related methods of analysis as well as distance measures are developed to identify homogeneous customers on the basis of their dynamic shopping behaviour. Subsequently, existing vector-based methods of classification and clustering are extended by these behaviour-related methods and measures. In addition, methods are developed to assign anonymous receipts to given customer groups in order to extent customer-related simulation results to anonymous customers of a company. Benefits and quality of the developed models, methods and measures, which are implemented within a complex software system, are shown by practical examples and evaluated in several case studies — based on real data from a German retailer

Prospective on Automation for Omnichannel Services and the Need for New Robotic Solutions for Store Fulfillment Operations

As businesses offer omnichannel services, such as buy-online-pickup-in-store, more logistical processes need to be conducted within or close to a retail environment. For retailers who adopt a store fulfillment concept, order picking for online orders is conducted inside a store environment and is in addition to the logistic processes required to support in-store customer requests. A store fulfillment approach has the advantage of enabling inventory, labor, infrastructure, and automation to be pooled for online orders, in-store customers, and return processing. Yet, the design and operation of logistical tasks completed in a retail environment is more challenging and requires considering the salient features that vary from a distribution environment. This work provides an overview of omnichannel logistical processes and connects their unique features to open challenges in automating these processes. A benchmarking and classification study describes the state of the practice in 2022 in automated picking solutions. We find that the current market for automated picking solutions that could support a microfulfillment strategy is more mature than solutions that could support a store fulfillment strategy. We identify a set of design and technical requirements for an automated picking solution deployed in a retail environment to support store fulfillment. Moveable robotic piece-level picking solutions need to become more flexible so that they can accommodate different item types, store shelf designs, facility layouts, logistical tasks, and human interactions, as well as more agile so they can robustly operate in uncertain and new environments

How governments strategically time welfare state reform legislation: empirical evidence from five European countries

Building on studies on the political business cycle, the literature on welfare state retrenchment has argued that governments which cut the welfare state try to avoid blame by implementing painful measures in the beginning of the mandate and expanding benefits as elections approach. In contrast to this linear relationship, we argue that governments often feel pressured to fulfill (mostly expansionary) campaign promises during the first months in office. Consequently, cutting right away is not what should be expected. Instead, a more nuanced, u-shaped timing trajectory is probable with a period in the beginning characterized by both cuts and fulfillment of expansionary pledges, followed by a period of cutbacks, and finally an expansive phase toward the end of a mandate. We test this argument on a new original dataset of legislative changes in five European countries – Britain, Denmark, Finland, France, and Germany – during the last four decades

Hvordan reagerer vælgerne på velfærdsreformer?

I velfærdsstatslitteraturen diskuteres det, om reformer påvirker opbakningen til den siddende regering. Vi har indsamlet årligt data på velfærdsreformer af pensions- og arbejdsløshedsområderne og meningsmålinger i Storbritannien helt tilbage til 1946. Det giver os mulighed for at teste statistisk, hvorvidt velfærdsreformer påvirker regeringens folkelige opbakning. Det viser sig, at det gør de. Nedskæringer fører til lavere støtte, men ekspansion fører til højere støtte. Ikke mindst det sidste er interessant, fordi man i litteraturen ofte fokuserer på nedskæringer. Vores analyse tyder på, at der er et næsten symmetrisk forhold, således at effekten af nedskæringer og ekspansion er nogenlunde lige stor, men altså i forskellige retninger

Universal Basic Income Roundtable

The Margaret Chase Smith Policy Center invited local, regional, and international experts on universal basic income (UBI) to participate in a new feature: Maine Policy Perspectives. In total, the perspectives of seven individuals are included in this roundtable regarding UBI.https://digitalcommons.library.umaine.edu/mcspc_perspectives/1000/thumbnail.jp