The democratic challenges and potential of localism: insights from deliberative democracy

This article considers the democratic challenges and potential of localism by drawing on insights from the theory and practice of deliberative democracy. On a conceptual level, the ideas embedded in localism and deliberative democracy share much in common, particularly the democratic goal of engaging citizens in decisions that affect them. Despite such commonalities, however, there has been limited conversation between relevant literatures. The article considers four democratic challenges facing localism and offers a response from a systems perspective of deliberative democracy. It argues that, for localism to realise its democratic potential, new participatory spaces are required and the design of these spaces matters. Beyond structured participatory forums, local democracy also needs an active and vibrant public sphere that promotes multiple forms of democratic expression. This requires taking seriously the democratic contributions of local associations and social movements. Finally, the article argues that, to fulfil its democratic potential, localism needs to encourage greater democratic and political connectivity between participatory forums and the broader public sphere.     

Dynamic Capability Building in Service Value Networks for Achieving Service Innovation

Service organizations increasingly create new service offerings that are the result of collaborative arrangements operating on a value network level. This leads to the notion of “elevated service offerings,” our definition of service innovation, implying new or enhanced service offerings that can only be eventuated as a result of partnering, and one that could not be delivered on individual organizational merits. Using empirical data from a large telecommunications company, we demonstrate through structural equation modeling (SEM) that higher‐order dynamic capabilities in services are generated as a result of collaboration between stakeholders. Furthermore, it is through collaboration and education of the stakeholders that additional higher‐order capabilities emerge (customer engagement [CuE], collaborative agility [CA], entrepreneurial alertness [EA], and collaborative innovative capacity), all of which influence the service innovation outcome. Our study also reveals empirical evidence for an ongoing process of continuous dynamic capability building in accordance with the changing dynamics of business. Managers of service organizations should recognize the potential embedded in these higher‐order skill sets, starting from collaboration, learning, and management of creative ideas for both strategic and operational benefits. Moreover, the capabilities of CA, EA, and CuE are even more important in managing the flexibility, timely delivery, and reliability of service offerings. Managers should take measures to inculcate, promote, and manage these dynamic capability skill sets to foster innovation in services.     

A Monte Carlo-based pseudo-coefficient of determination for generalized linear models with binary outcome

In this article, we focus on a pseudo-coefficient of determination for generalized linear models with binary outcome. Although there are numerous coefficients of determination proposed in the literature, none of them is identified as the best in terms of estimation accuracy, or incorporates all desired characteristics of a precise coefficient of determination. Considering this, we propose a new coefficient of determination by using a computational Monte Carlo approach, and exhibit main characteristics of the proposed coefficient of determination both analytically and numerically. We evaluate and compare performances of the proposed and nine existing coefficients of determination by a comprehensive Monte Carlo simulation study. The proposed measure is found superior to the existent measures when dependent variable is balanced or moderately unbalanced for probit, logit, and complementary log–log link functions and a wide range of sample sizes. Due to the extensive design space of our simulation study, we identify new conditions in which previously recommended coefficients of determination should be used carefully.     

The snowball effect of customer slowdown in critical many-server systems

Customer slowdown describes the phenomenon that a customer’s service requirement increases with experienced delay. In healthcare settings, there is substantial empirical evidence for slowdown, particularly when a patient’s delay exceeds a certain threshold. For such threshold slowdown situations, we design and analyze a many-server system that leads to a two-dimensional Markov process. Analysis of this system leads to insights into the potentially detrimental effects of slowdown, especially in heavy-traffic conditions. We quantify the consequences of underprovisioning due to neglecting slowdown, demonstrate the presence of a subtle bistable system behavior, and discuss in detail the snowball effect: A delayed customer has an increased service requirement, causing longer delays for other customers, who in turn due to slowdown might require longer service times.     

The odd log-logistic Lindley Poisson model for lifetime data

We define two new lifetime models called the odd log-logistic Lindley (OLL-L) and odd log-logistic Lindley Poisson (OLL-LP) distributions with various hazard rate shapes such as increasing, decreasing, upside-down bathtub, and bathtub. Various structural properties are derived. Certain characterizations of OLL-L distribution are presented. The maximum likelihood estimators of the unknown parameters are obtained. We propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest has a Poisson distribution and the time to event has an OLL-L distribution. The applicability of the new models is illustrated by means real datasets.