On commodification: volunteer experiences in festivals†

This paper is about the creation of non-commodified volunteer experiences, for tourists and local volunteers participating in festivals. How is the tourist experience created when most of the traditional tourism demands are not fulfilled? And what are the experiences and how do they relate to different ‘regimes of value’? The experience context includes tourists who work together with locals voluntarily in a festival, where the volunteers pay for their own travel, food, overnight stay, and work for free. To gain more knowledge on the volunteers is important because local cultural life becomes more festivalized, most festivals are reliant on the involvement of volunteers, and the festivals gain an important role in an economy where even small places are engaged in branding [Löfgren, O. 2003. The new economy: A cultural history. Global Networks, 3, 239–254]. This paper uses a qualitative approach. Interviews were conducted (n?=?23) and participants were observed during four festivals in Finnmark, Norway. Nothing in the experiences was facilitated, and the experience creation occurred in the work tasks together with volunteer colleagues. It was like a holiday experience, without a stream of commodified moments. It was a value creation that could be seen as authentic and real, created in the interaction between the local and visiting volunteers.     

Exploring the possibilities for causal explanation in interpretive research

This paper suggests how the contemporary theory of causality, based on the notions of counterfactuality and contrastive thinking, offers helpful direction on how to generate plausible causal arguments in interpretive research. For an interpretive researcher, this opens a route from rich emic accounts to thick explanations; however, only if he/she so wishes and the research question so requires. Perhaps with some surprise, causality can be included in interpretive research framings without compromising the unique features of such research – actually by even building on some of its strongholds. Examples from interpretive management accounting research will illustrate the message of the paper.     

Generative Mechanisms of the Adoption of Logistics Innovation: The Case of On‐site Shops in Construction Supply Chains

Empirical studies of logistics innovations have focused on the innovation process, bypassing much the innovative artifact or solution design itself. Focusing on the artifact and solution design in a case study, we contribute to the emerging theory of logistics innovations through articulating the generative mechanisms of the adoption of logistics innovation, that is, the mechanisms through which the design of the solution enables its adoption. We study On‐site Shop, a rare example from the construction industry of a logistics innovation that has successfully migrated from a limited number of pilots to common practice. The case study is based on insights from participation in the design of the solution, and on 55 interviews conducted in a relationship triad consisting of three groups: (1) construction site users, (2) the solution designers, and (3) the suppliers. We propose that standard and efficient solution set‐up is the key enabler of logistics innovation's adoption at temporary construction sites. Communication and operating rules facilitate adoption in the triad, whereas internal and external integration further advance adoption by creating links between the innovative logistics solution and other activities. Finally, trilateral collaboration and congruent technological frames in the relationship triad sustain adoption over time.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.     

Budget impact analysis of secukinumab versus adalimumab in the treatment of ankylosing spondylitis

Background: Biologic treatments have enhanced the treatment outcomes of patients with active ankylosing spondylitis (AS). Until recently, TNF-alpha-inhibitors have been the only biologics approved for the treatment of active AS. The objective of this study was to assess the potential financial impact of the first non-TNF-alpha biologic secukinumab (fully human IL-17A-inhibitor) vs adalimumab (TNF-alpha-inhibitor) in the treatment of AS in Finland.

Materials and methods: In this model-based budget impact analysis, patients were treated either with secukinumab (150?mg) or adalimumab (40?mg). The number of patients and market share of different biologics were based on national reimbursement registry data. Adalimumab was the most commonly used biologic treatment for AS, and in the base case analysis all adalimumab patients are assumed to switch to secukinumab. Response rates were based on a matching-adjusted indirect comparison between secukinumab and adalimumab. Patients not achieving response were switched to another biologic treatment.

Results: Treating AS patients with secukinumab instead of adalimumab leads to potential savings of 18.2 million euros within a 5-year time period. The total costs within the follow-up time were 59.5 million euros and 77.7 million euros with and without secukinumab, respectively. According to sensitivity analyses, a higher adoption rate of secukinumab corresponds to higher potential savings.

Conclusions: Secukinumab is a cost-saving treatment option compared with adalimumab in the treatment of AS in Finland. More patients could be treated with a biologic by allocating resources more efficiently.     

The Learning Process in Technology Entrepreneurship Education—Insights from an Engineering Degree

We propose a model for the learning process in technology entrepreneurship based on the findings from an in‐depth case study of an engineering degree that emphasizes technology entrepreneurship. Taking learning paradigms from entrepreneurship education into account, we specify the links between pedagogical approaches, activities, and learning contexts and specific technology entrepreneurship learning outcomes. For example, we examine how the use of existential learning with self‐directed activities in real‐world contexts contributes to achieving high‐level entrepreneurial competencies such as the ability to critically self‐reflect on the choices made by the technology‐based venture. As such, we contribute to the definition of teaching models for technology entrepreneurship education.     

The Challenge of Obtaining Quality Care: Limited Consumer Sovereignty in Human Services

Abstract

This paper offers a conceptual analysis of the problem of quality in human services: in elementary school, psychiatric care, and the health and social care of children, the elderly, and the intellectually disabled. Geriatric nursing home patients are used as a case. These care recipients cannot enforce their legal right to quality service; their quality-effective demand is low. Formal economic analyses often characterize the weak position of the care recipient as an information asymmetry problem. An additional obstacle, however, is the recipient's inability to safeguard her personal interest due to physical, mental, or social incapacities; that is, “limited consumer sovereignty.” Incapacitated individuals cannot enforce quality even when quality information is available. This creates a fundamental incentive problem in the monitoring of quality. They also depend on services that are complex and non-verifiable, making external monitoring difficult. This paper presents a typology of measures to increase the quality pressure facing providers.     

On The Log-Linear Analysis Of Multiple Response Data

Log-linear procedures have been recommended for analyzing data that are in the form of counts or frequencies (Iacobucci and McGill 1990). In its current form, the recommended procedure does not deal with multiple response data (i.e., more than one thought per response category). The paper proposes analytical modifications that researchers need to consider when fitting models with this type of data. The problems and recommended modifications are illustrated with two distinct data sets. The first involves consumers' attribution responses to negative word-of-mouth communication about a brand whereas the second pertains to consumers' cognitive responses toward an advertisement. Results in each case indicate that researchers may generate erroneous conclusions about the significance of estimated parameters if the recommendations are ignored.     

Dynamic portfolio optimization across hidden market regimes

Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational advantages to using MPC when estimates of future returns are updated every time a new observation becomes available, since the optimal control actions are reconsidered anyway. MPC outperforms a static decision rule for changing the allocation and realizes both a higher return and a significantly lower risk than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces the number of trades is found to increase the robustness of the approach.