Pricing of Full‐Service Repair Contracts with Learning,Optimized Maintenance,and Information Asymmetry

This article considers the optimal pricing of full‐service (FS) repair contracts by taking into account learning and maintenance efficiency effects, competition from service , and asymmetric information. We analyze on‐call service (OS) and FS contracts in a market where customers exhibit heterogeneous risk aversion. While the customers minimize their disutility over the equipment lifetime, the service provider maximizes expected profits arising from the portfolio of OS and FS contracts. We show that the optimal FS price depends inter alia on the customer's prior cost experience and on OS repair and maintenance costs. The optimal FS price is shown to increase as fewer OS customers are lost to competition, whereas improved repair learning enabled by FS reduces the optimal price. A numerical study based on data from a manufacturer of forklifts highlights the importance of learning in maintenance operations, which constitutes the key benefit of FS contracts; 81% of the customers select the FS option and are willing to pay an insurance premium of around 1.5% of total OS cost against volatility of repair costs.     

Opt‐Out Options in New Product Co‐development Partnerships

We study three contractual arrangements—co‐development, licensing, and co‐development with opt‐out options—for the joint development of new products between a small and financially constrained innovator firm and a large technology company, as in the case of a biotech innovator and a major pharma company. We formulate our arguments in the context of a two‐stage model, characterized by technical risk and stochastically changing cost and revenue projections. The model captures the main disadvantages of traditional co‐development and licensing arrangements: in co‐development the small firm runs a risk of running out of capital as future costs rise, while licensing for milestone and royalty (M&R) payments, which eliminates the latter risk, introduces inefficiency, as profitable projects might be abandoned. Counter to intuition we show that the biotech's payoff in a licensing contract is not monotonically increasing in the M&R terms. We also show that an option clause in a co‐development contract that gives the small firm the right but not the obligation to opt out of co‐development and into a pre‐agreed licensing arrangement avoids the problems associated with fully committed co‐development or licensing: the probability that the small firm will run out of capital is greatly reduced or completely eliminated and profitable projects are never abandoned.     

Partisan ideology,veto players and their combined effect on productive and protective welfare policy: how the left still matters after all?

Quantitative analysis of the question whether ‘parties still matter’ has largely focused on the dynamics of aggregated expenditure-based dependent variables or protective welfare policies such as unemployment, sickness and family benefits. This article develops a series of pooled time-series cross-section regression specifications predicting changes in disaggregated protective welfare policies alongside productive welfare policies, namely family services, active labour market programmes and public education, across 17 Western democracies (1971–2010). In so doing, it employs the latest Comparative Manifesto Project [Volkens, A., P. Lehmann, N. Merz, S. Regel, and A. Werner. 2014. The Manifesto Data Collection. Manifesto Project (MRG/CMP/MARPOR). Version 2014b. Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB). Accessed January 2015. https://manifestoproject.wzb.eu/information/information] and Veto Player [Jahn, D., T. Behm, N. Düpont, and C. Oberst. 2012. Parties, Institutions & Preferences: Veto Player (Annual), Version 2012–02. Accessed January 2015. http://comparativepolitics.uni-greifswald.de/data.html] data to explore the effect of the ideological position of prime ministers’ parties, veto players and their combined effect on these welfare policy areas. The article confirms that Left and Right governments ceased to make any substantive difference for protective welfare policies from the early 1980s onwards. Yet, it also finds that positive Left partisan effects have largely persisted for productive welfare policies. In the era of global competition, Left party ideology has continued to be an important factor in realising a social investment perspective in practice; in terms of the expansion of family services, its effects have been contingent on the veto power Left prime ministers faced.     

Access to and exclusion from housing over time: Refugees' experiences in rural areas

Taking the example of recognized refugees in rural Germany, and following the housing pathways approach, the paper addresses the complex interplay of individual and family-related residential preferences over time as well as structural factors regarding access to housing and associated settlement and integration. Results are from a long-term empirical study that encompassed both refugees’ and local actors’ views. Mechanisms and practices of exclusion that prevent refugees from accessing appropriate private housing are related to the negotiation of residential preferences about where and how to live, as well as to structural aspects such as the pattern of local housing markets, accessibility of infrastructures or the unwillingness of landlords to let to refugees. The paper concludes to highlight the role of place in housing trajectories and the significance of social resources within refugees' practices and local intermediaries' strategies to overcome exclusion and provision of access to rural housing.     

The Steiner cycle and path cover problem on interval graphs

The Steiner path problem is a common generalization of the Steiner tree and the Hamiltonian path problem, in which we have to decide if for a given graph there exists a path visiting a fixed set of terminals. In the Steiner cycle problem we look for a cycle visiting all terminals instead of a path. The Steiner path cover problem is an optimization variant of the Steiner path problem generalizing the path cover problem, in which one has to cover all terminals with a minimum number of paths. We study those problems for the special class of interval graphs. We present linear time algorithms for both the Steiner path cover problem and the Steiner cycle problem on interval graphs given as endpoint sorted lists. The main contribution is a lemma showing that backward steps to non-Steiner intervals are never necessary. Furthermore, we show how to integrate this modification to the deferred-query technique of Chang et al. to obtain the linear running times.

     

Bringing Indonesia into the global welfare regime debate: A literature review and future research agenda

Studies on welfare state regimes have been dominated by consideration of rich OECD/European and increasingly East Asian countries/territories, leaving South Asian cases such as Indonesia underexplored. The few existing studies that have explicitly tried to conceptualize the Indonesian welfare regime have resulted in little consensus. To address the resulting lack of clarity, this article reviews scholarly articles relevant to bringing Indonesia into the global welfare regime debate, specifically encapsulating how the country has been classified compared with its East Asia counterparts. Accordingly, we find that existing studies have mainly concentrated on the Indonesian health care and social protection expansion, which has led authors to conclude that this evolution demonstrates Indonesia's transition away from welfare productivism. By contrast, we argue that Indonesia's productivist characteristics have largely prevailed while informal networks, clientelism, strong families, and the limited effectiveness of the civil society movement created a specific social politics in Indonesia. We thus conclude that the causal mechanisms typically attributed to welfare development in more developed welfare geographies, including East Asia, cannot fully explain the evident institutional formation in the Indonesian case. The future research agenda for studying the welfare regimes in Indonesia and other Southeast Asian countries is discussed.     

Defining estimands for efficacy assessment in single arm phase 1b or phase 2 clinical trials in oncology early development

The addendum of the ICH E9 guideline on the statistical principles for clinical trials introduced the estimand framework. The framework is designed to strengthen the dialog between different stakeholders, to introduce greater clarity in the clinical trial objectives and to provide alignment between the estimand and statistical analysis. Estimand framework related publications thus far have mainly focused on randomized clinical trials. The intention of the Early Development Estimand Nexus (EDEN), a task force of the cross-industry Oncology Estimand Working Group ( www.oncoestimand.org ), is to apply it to single arms Phase 1b or Phase 2 trials designed to detect a treatment-related efficacy signal, typically measured by objective response rate. Key recommendations regarding the estimand attributes include that in a single arm early clinical trial, the treatment attribute should start when the first dose is received by the participant. Focusing on the estimation of an absolute effect, the population-level summary measure should reflect only the property used for the estimation. Another major component introduced in the ICH E9 addendum is the definition of intercurrent events and the associated possible ways to handle them. Different strategies reflect different clinical questions of interest that can be answered based on the journeys an individual subject can take during a trial. We provide detailed strategy recommendations for intercurrent events typically seen in early-stage oncology. We highlight where implicit assumptions should be made transparent as whenever follow-up is suspended, a while-on-treatment strategy is implied.     

Intermediaries in the relevance-gap debate: A systematic review of consulting roles

A highly contested issue in management science is its relevance to practice. Despite third parties’ potentially significant role in changing the interaction between divided parties, the long-standing literature on the relevance gap has paid third parties little systematic attention. Drawing on a boundary-spanning perspective, and the concept of brokerage in particular, we review how the consultant role is discussed as an intermediary third party between management science and management practice. Based on a systematic literature review of 133 articles, we identify different intermediary consultant roles linking management science to management practice. Our findings detail how the practices associated with intermediary consultant roles performed by academics or practitioners relate to several key relevance criteria, how management knowledge flows when including intermediaries and how intermediaries in different roles relate to different audiences. Based on the findings, we develop a third-party model of intermediary consultant roles and knowledge flows. The model indicates the theoretical significance of third parties in shaping the interaction and knowledge flows between management science and management practice and has theoretical implications for understanding the persistence of the relevance gap. Regarding practical implications, we suggest how management scientists could target third parties as new key practitioner audiences. Considering third parties, and thus moving away from a two-party view, opens up promising directions for further research on the roles and role shifts of various intermediary actors and on how different intermediary audiences may appreciate different types of academic knowledge.     

Robust optimal estimation of location from discretely sampled functional data

Estimating location is a central problem in functional data analysis, yet most current estimation procedures either unrealistically assume completely observed trajectories or lack robustness with respect to the many kinds of anomalies one can encounter in the functional setting. To remedy these deficiencies we introduce the first class of optimal robust location estimators based on discretely sampled functional data. The proposed method is based on M-type smoothing spline estimation with repeated measurements and is suitable for both commonly and independently observed trajectories that are subject to measurement error. We show that under suitable assumptions the proposed family of estimators is minimax rate optimal both for commonly and independently observed trajectories and we illustrate its highly competitive performance and practical usefulness in a Monte-Carlo study and a real-data example involving recent Covid-19 data.