EconStor (ZBW Kiel)
Not a member yet
310344 research outputs found
Sort by
Unpacking olfactory marketing: initial evidence for the positive effects of scented parcels on post-order consumer responses in e-commerce
No full textAbstract
Can the scent of a parcel influence post-order consumer responses in e-commerce? This study presents initial evidence for the untapped potential of olfactory marketing in online retail. We conducted an incentivized laboratory experiment in which participants received either scented or unscented parcels containing a product from a fictional outdoor sports brand. The results demonstrate that scented parcels significantly improve the unpacking experience, product evaluation, and brand perception, including green brand equity. Furthermore, scented parcels increase post-order willingness to pay. Our findings lay the foundation for exploring olfactory marketing in digital retail settings and offer practical insights for online retailers. We conclude our report by discussing potential moderating factors and identify further research questions
“They Don’t Have the Time for That, Participating in Politics” - How Local Politicians Interpret Political Integration in the USA
No full textAbstract
Political integration is an important aspect of immigrant integration because it strengthens ties with the host country’s political institutions. In particular, the local level is often the first step for immigrants to become politically engaged as they feel that they have a stake in the city, and, indeed, many diverse cities position themselves as advocates of immigrant rights. However, we know little about how local politicians interpret the political integration of immigrants in their communities. To identify key patterns in their interpretations, I conducted 20 qualitative interviews with local politicians and administrative employees in Maryland and Washington, D.C. and analyzed them using Bohnsack’s documentary method. Specifically, I compare immigrant and non-immigrant local politicians and administrative employees. Overall, immigrant and non-immigrant local politicians differ in their views of the relationship between immigrants and political integration. While immigrant local politicians conceive political integration and other forms of integration, such as labor market integration, as equally important, non-immigrant politicians view political integration as subordinate to other forms of integration. Moreover, immigrants are described as inherently mistrusting of politics, both due to their political socialization and current US politics. Thus, this study sheds further light on how local politicians interpret immigrant political integration in the USA
Enable and orchestrate—How keystone actors shape institutions for smart service innovation in ecosystems
No full textAbstract
This study explores the role of keystone actors in shaping institutions to drive collaborative innovation within service ecosystems, focusing on smart services in industrial B2B settings. Smart services leverage data analytics for enhanced customer insights, marking a strategic shift for product-oriented companies. Transitioning to smart services involves adapting business models and fostering effective collaborations. Keystone actors facilitate this by promoting collaboration and aligning participants toward shared goals without exerting direct control. While previous research emphasizes understanding keystone actors in service ecosystems, how they shape institutions for collaboration is rarely investigated. This study aims to provide insights into driving smart service innovation, enhancing companies’ competitive advantage in the digital era. Using a multiple case study design, the research identifies two keystone actor types: the Orchestrator and the Enabler. The findings offer valuable insights into institution shaping and keystone actors’ influence, guiding practitioners in managing smart service innovation. O3;O3
The Road to Gaza: A Preface
Full text linkהסיבה הישירה למלחמה בעזה ידועה לכול אדם נאור והיא מסתכמת במילים פשוטות: הכיבוש הישראלי המתמשך שגורם להתפרצויות מרי מחזוריות [...] אם מחפשים סיבות ארוכות טווח יותר, אף הן מסתכמות במילים פשוטות: הקולוניזציה הציונית האגרסיבית בחסות המעצמות הגדולות מאז ראשית המאה ה-20, שגוררת את כלל מדינות המזרח התיכון לתוך מעגל הקונפליקט בין ישראל לבין סביבתה [...] אבל הספר הזה -- הדרך לעזה: על משטרי הכוח וכנסיות האל העליון היחיד (2024) -- אינו עוסק רק בסיבות הישירות למלחמות ולקונפליקטים הצבאיים בין ישראל לבין הפלסטינים ומדינות ערב. הספר מעוניין לספר על הדרך הארוכה שהובילה באופן בלתי נמנע (לכאורה) אל המלחמה בעזה. מדובר במסע בן ששת אלפי שנים שמקפל בתוכו הרבה יותר מאשר עטיפה חיצונית רעשנית המציגה מלחמת קודש בין מיליציות רבניות לבין מליציות איסלמיות
Can Copyright Law Benefit from the Marking Requirement of the AI Act?
No full textAbstract
Advancements in generative artificial intelligence (AI) have raised significant challenges for copyright law. These include the issue of distinguishing between copyrightable and non-copyrightable AI-based output and the risk of copyfraud. One potential solution that might be envisaged in this regard is to subject non-copyrightable AI-based output to a transparency obligation. While these questions remain a topic of debate within copyright law, an answer may have already crystallised beyond its boundaries. In this vein, the article attempts to elucidate whether copyright law, in its quest to address the complexities at hand, can benefit from the marking requirement under Art. 50(2) AI Act. To this end, the article provides an overview of this provision, explores the technical and legal challenges associated with it, and analyses its prospects for copyright law. The article concludes that, despite its appeal, Art. 50(2) AI Act is unlikely to constitute a solution for differentiating between copyrightable and non-copyrightable AI-based output and combating copyfraud, and points to other approaches that are being discussed in this context
Comparing loading strategies for auto-trains: balancing efficiency with information requirements
No full textAbstract
Auto-trains serve as the favored transportation mode for distributing passenger vehicles, offering cost-effective and environmental benefits over transportation by trucks. This paper addresses the auto-train loading problem (ATLP) with the objective to improve the capacity utilization of auto-trains. We propose five different problem cases of the ATLP with varying levels of available information on the availability and accessibility of the vehicles and develop suitable strategies to solve them. This paper proposes the first contribution to the ATLP in the domain of finished vehicle logistics. The ATLP differs from similar problems, such as the motorail transportation problem, as it involves various precedence constraints. We consider the method and order in which the vehicles are parked as well as the order in which they are loaded on the auto-train. For the first two cases, we approach the problem as a multiple knapsack problem and solve it heuristically using a best-fit algorithm. For the other three cases, we formulate the ATLP as a generalized assignment problem and solve it with a commercial solver. We also develop a rolling-horizon heuristic to address the problem’s size for two of these cases. This research contributes by formally defining the ATLP, offering a spectrum of strategies tailored to varying levels of information, and conducting simulations based on real-world data to quantify potential improvements. The findings indicate that, on average, the objective value of strategies for cases with less available information aligns with historical data, while our strategies for cases with higher information could increase capacity utilization by up to 9.73% compared to historical data
Muyang Chen. 2024. The Latecomer’s Rise: Policy Banks and the Globalization of China’s Development Finance. (Ithaca, NY: Cornell University Press)
No full textbook revie
Burden of Disease in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Scoping Review
No full textAbstract
Objective
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a serious chronic and complex multi-system disease characterised by symptoms such as post-exertional malaise, fatigue, cognitive impairment and pain. Diagnosis is based on international consensus criteria, and no curative treatment is available. In the USA, its prevalence is estimated at 0.42% among adults, with women affected three times as often as men. Prevalence is expected to increase due to the COVID-19 pandemic. In addition to its severe symptoms, ME/CFS has a substantial economic impact. This scoping review aimed to systematically examine the global health, social and economic burden of ME/CFS.
Methods
We conducted a systematic literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines in six databases and supplemented it with a citation search. We assessed study quality using a modified version of the Mixed Methods Appraisal Tool.
Results
We included 20 studies that assessed costs ( n = 16), disability-adjusted life years (DALYs) (n = 3), employment rates ( n = 1), and school attendance ( n = 1) as indicators of disease burden. Reported costs per patient ranged from USD 2,916 to USD 119,611, with indirect costs accounting for the largest proportion. DALYs reported for the USA ranged from 0.714 million in 2016 to 5.77 million in 2022.
Conclusion
ME/CFS imposes a substantial health, social and economic burden of disease. Discrepancies in estimates are probably due to differences in study samples, methodologies, cost components, and healthcare systems. Because ME/CFS is assumed to be underdiagnosed, its true burden may be even higher
Can Gamification Foster Trust-Building in Human-Robot Collaboration? An Experiment in Virtual Reality
No full textAbstract
With the increasing deployment of robots to support humans in various activities, a crucial factor that has surfaced as a precondition for successful human-robot interaction (HRI) is the human’s level of trust in the robotic companion. A phenomenon that has recently shifted into the foreground for its potential to influence cognitive and affective dimensions in humans is gamification. However, there is a dearth of knowledge whether and how gamification can be employed to effectively cultivate trust in HRI. The present study investigates and compares the effects of three design interventions (i.e., non-gamified vs. gameful design vs. playful design) on cognitive and affective trust between humans and an autonomous mobile collaborative robot (cobot) in a virtual reality (VR) training experiment. The results reveal that affective trust and specific trust antecedents (i.e., a robot’s likability and perceived intelligence) are most significantly developed via playful design, revealing the importance of incorporating playful elements into a robot’s appearance, demeanor, and interaction to establish an emotional connection and trust in HRI
Validating an Index of Selection Bias for Proportions in Non‐Probability Samples
Full text linkSummary
Fast online surveys without sampling frames are becoming increasingly important in survey research. Their recruitment methods result in non‐probability samples. As the mechanism of data generation is always unknown in such samples, the problem of non‐ignorability arises making vgeneralisation of calculated statistics to the population of interest highly questionable. Sensitivity analyses provide a valuable tool to deal with non‐ignorability. They capture the impact of different sample selection mechanisms on target statistics. In 2019, Andridge and colleagues proposed an index to quantify potential (non‐ignorable) selection bias in proportions that combines the effects of different selection mechanisms. In this paper, we validate this index with an artificial non‐probability sample generated from a large empirical data set and additionally applied it to proportions estimated from data on current political attitudes arising from a real non‐probability sample selected via River sampling. We find a number of conditions that must be met for the index to perform meaningfully. When these requirements are fulfilled, the index shows an overall good performance in both of our applications in detecting and correcting present selection bias in estimated proportions. Thus, it provides a powerful measure for evaluating the robustness of results obtained from non‐probability samples