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Decision Making in Psychiatric Reform: A Case Study of the Czech Experience

Abstract

This study examines the initial impact of a broadly participatory planning process in the Czech Republic during 2016–2017, aimed at both reducing inpatient care and expanding community mental health systems, on policy and programmatic decision making. A central focus of the study involves the trade-offs between and efforts to integrate shared decision making with evidence-based planning methods within the context of a national psychiatric reform strategy, particularly one involving a former Soviet bloc state.

Given the uniqueness of the Czech experience, an exploratory case study methodology is used, one involving ten interviews with key informants and examination of a wide variety of documents. Results include the development of broad new decision and oversight structures, and the initial implementation of community mental health services. The nation faces some of the same trade-offs found elsewhere, such as in the United States, between an inclusive participatory process, and one that systematically incorporates empirical rational and evidence and best practices within bounded parameters.

Implications for new psychiatric deinstitutionalization initiatives are identified, including development of a national mental health authority, a professional workforce, new funding strategies, multi-level service coordination, mechanisms to assure transparency, among others.

Open access
The fuzzy concept of collaborative governance: A systematic review of the state of the art

Abstract

This article contributes to the consolidation and synthesis of scholarship on collaborative governance by expanding our knowledge of how the term is used in the academic literature and policy documents in a range of European countries. It adds value to the existing reviews of the field by conducting a systematic literature review on a corpus of over 700 article abstracts and a traditional literature review identifying five key analytical dimensions. The article also provides an exploratory analysis of grey literature hitherto outside the purview of researchers and considers the linguistic and cultural connotations that alter the meaning of the term when translated into new contexts in ten EU/EFTA countries. Findings indicate heterogeneity and fuzziness in the way the concept is used. The article argues that explicit positions with respect to five main analytical dimensions and taking into account the national connotations that the term carries across political systems would inject more clarity into the academic discourse. This, in turn, will help policymakers to make informed use of the concept, especially in multi-national policy-making arenas.

Open access
The influence of age factors on the reform of the public service of Ukraine

Abstract

It had been established that the heads of institutions should form teams of workers of different generations with different expectations and methods of work in the context of reforming the public service. The periods of forming generations have been set on the basis of literary sources, such as: Generation X (the period up to 1980); Generation Y (from 1981 to 1996); and Generation Z (after 1997). The most important criteria which form the characteristics of public servants have been singled out, and common and distinctive traits of Generations X, Y, and Z have been systematized. The distribution of the number of public servants in Ukraine has been analyzed by gender, age and the category of position. Based on the use of correlation-regression analysis, the tendency of changes in the share of state servants of Ukraine by age category up to 2020 was investigated. This made it possible to confirm the suggested hypothesis of the dependence of the effective reform of the Ukrainian public service on the effective interaction and cooperation of all generations of public servants. The main requirements for a public institution in which the employees of the new generation will work have been systematized.

Open access
AI-Driven Sales Automation: Using Chatbots to Boost Sales

Abstract

The implementation of bot interfaces varies tremendously in current industry practice. They range from the human-like to those that merely present a brand logo or a digital avatar. Some applications provide a maximum amount of information with limited turn-taking between the user and the interface; others offer only short pieces of information and require more turn-taking. Instead of simply implementing the default option provided by chatbot providers and platforms, companies should consider very carefully how the specifics of the chatbot interface might affect the user experience. Simple mechanics such as increasing the frequency of interactions leads to greater trust and a more enjoyable user experience. Also, personalizing chatbots with basic consumer characteristics such as gender increases trust and improves the perceived closeness between the customer and the chatbot – and ultimately the brand. Brand managers should therefore consider chatbots not as merely another digital marketing fad or a way to save costs through service automation. When implemented wisely, they are even able to increase a company’s upselling potential.

Open access
Editorial
Open access
Let the Machine Decide: When Consumers Trust or Distrust Algorithms

Abstract

Thanks to the rapid progress in the field of artificial intelligence algorithms are able to accomplish an increasingly comprehensive list of tasks, and often they achieve better results than human experts. Nevertheless, many consumers have ambivalent feelings towards algorithms and tend to trust humans more than they trust machines. Especially when tasks are perceived as subjective, consumers often assume that algorithms will be less effective, even if this belief is getting more and more inaccurate.

To encourage algorithm adoption, managers should provide empirical evidence of the algorithm’s superior performance relative to humans. Given that consumers trust in the cognitive capabilities of algorithms, another way to increase trust is to demonstrate that these capabilities are relevant for the task in question. Further, explaining that algorithms can detect and understand human emotions can enhance adoption of algorithms for subjective tasks.

Open access
The Machine Age of Marketing: How Artificial Intelligence Changes the Way People Think, Act, and Decide

Abstract

Whatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms that process this data.

AI has the potential to make our life easier, but this convenience might come at a price which we have to pay such as biases directly built-in to the algorithms we use, data privacy issues or failed AI projects in business practice. But without testing, failing, and learning from our failures, there

Open access
Talking Versus Typing: The Power of Voice-Based Remote Controls
Interview with Jan Neumann, Senior Director, Applied AI, Comcast Cable, Philadelphia, USA

Abstract

While many customers are still reluctant to entrust themselves to Alexa, Cortona or Siri in their homes, they seem to be less worried about controlling their TV sets via voice control. Comcast started offering a voice-based remote control in 2015 and has extended this service continuously. In the vast world of home entertainment, it seems that voice has come just in time to help consumers navigate and control their ever-increasing home entertainment options. Jan Neumann explains how Comcast enables its customers to comfortably boil down a huge entertainment portfolio to personally relevant content on the TV screen, and how the company remains successful in the highly competitive home entertainment market.

Open access
The Thorny Challenge of Making Moral Machines: Ethical Dilemmas with Self-Driving Cars

Abstract

The algorithms that control AVs will need to embed moral principles guiding their decisions in situations of unavoidable harm. Manufacturers and regulators are confronted with three potentially incompatible objectives: being consistent, not causing public outrage, and not discouraging buyers. The presented moral machine study is a step towards solving this problem as it tries to learn how people all over the world feel about the alternative decisions the AI of self-driving vehicles might have to make. The global study displayed broad agreement across regions regarding how to handle unavoidable accidents. To master the moral challenges, all stakeholders should embrace the topic of machine ethics: this is a unique opportunity to decide as a community what we believe to be right or wrong, and to make sure that machines, unlike humans, unerringly follow the agreed-upon moral preferences. The integration of autonomous cars will require a new social contract that provides clear guidelines about who is responsible for different kinds of accidents, how monitoring and enforcement will be performed, and how trust among all stakeholders can be engendered.

Open access
Understanding Consumer Preferences from Social Media Data

Abstract

Consumers produce enormous amounts of textual data of product reviews online. Artificial intelligence (AI) can help analyze this data and generate insights about consumer preferences and decision-making. A GfK research project tested how we can use AI to learn consumer preferences and predict choices from publicly available social media and review data. The common AI tool “Word Embeddings” was used and has shown to be a powerful way to analyze the words people use. It helped reveal consumers’ preferred brands, favorite features and main benefits. Language biases uncovered by the analysis can indicate preferences. Compared to actual sales data from GfK panels, they fit reasonably within various categories. Especially when data volumes were large, the method produced very accurate results. By using free, widespread online data it is completely passive, without affecting respondents or leading them into ranking or answering questions they would otherwise not even have thought of. The analysis is fast to run and no fancy processing power is needed.

Open access