Product and Process Innovations in a Horizontally Differentiated Product Market

For horizontal product differentiation, the paper examines the effects of the level of competition on the firm's decision between a product and process innovation. When firms have to choose between the two types of innovation, it is demonstrated that both firms undertake the product innovation when the competition is intense, they choose different investment projects in intermediate competition, and they pursue cost--reducing innovations when competition is less intense. If firms may pursue both innovations, they mix the types depending on the innovation cost structure. Again, firms incur higher costs into product innovations, when the competition is initially intense.Product innovation; Process innovation; Horizontal product differentiation

Do Anti-Dumping Rules Facilitate the Abuse of Market Dominance?

We discuss the effects of AD-protection in a standard Dixit model of entry deterrence. In an AD-regime, the newcomer is constrained by a minimum-price rule in addition to existing irreversible entrance costs. For minimum prices which lie below the Stackelberg one, we find that AD-rules distort competition. We show that AD-protection increases the advantages of entry deterrence for a wide range of combinations of sunk costs and minimum prices. When entrance costs are high, consumer welfare is lower in an AD-regime than under free trade. Consequently, AD-protection facilitates the abuse of market dominance.Anti-dumping; abuse of market dominance; strategic firm behaviour

Offline speech to text engine for delimited context in combination with an offline speech assistant

The inatura museum in Dornbirn had planned an interactive speech assistant-like exhibit. The concept was that visitors could ask the exhibit several questions that they would like to ask a flower. Solution requirements regarding the functionalities were formulated, such as the capacity to run offline because of privacy reasons. Due to the similarity of the exhibit, open-source offline Speech To Text (STT) engines and speech assistants were examined. Proprietary cloud-based STT engines associated with the corresponding speech assistants were also researched. The aim behind this was to evaluate the hypothesis of whether an open-source offline STT engine can compete with a proprietary cloud-based STT engine. Additionally, a suitable STT engine or speech assistant would need to be evaluated. Furthermore, analysis regarding the adaption possibilities of the STT models took place. After the technical analysis, the decision in favour of the STT engines called "Vosk" was made. This analysis was followed by attempts to adapt the model of Vosk. Vosk was compared to proprietary cloud-based Google Cloud Speech to Text to evaluate the hypothesis. The comparison resulted in not much of a significant difference between Vosk and Google Cloud Speech to Text. Due to this result, a recommendation to use Vosk for the exhibit was given. Due to the lack of intent parsing functionality, two algorithms called "text matching algorithm" and "text and keyword matching algorithm" were implemented and tested. This test proved that the text and keyword matching algorithm performed better, with an average success rate of 83.93 %. Consequently, this algorithm was recommended for the intent parsing of the exhibit. In the end, potential adaption possibilities for the algorithms were given, such as using a different string matching library. Some improvements regarding the exhibit were also presented.Das inatura Museum in Dornbirn hatte ein interaktives sprachassistentenähnliches Exponat geplant. Das Konzept sah vor, dass die Benutzenden dem Exponat verschiedene Fragen stellen können, die sie auch einer Blume stellen würden. Es wurden Lösungsanforderungen hinsichtlich der Funktionalitäten formuliert, wie z.B. die Fähigkeit, aus Datenschutzgründen offline zu laufen. Aufgrund der Ähnlichkeit des Exponats wurden Open-Source-Offline-STT-Engines und Sprachassistenten untersucht. Proprietäre Cloud-basierte STT-Engines in Verbindung mit den entsprechenden Sprachassistenten wurden ebenfalls untersucht. Ziel war es, die Hypothese zu evaluieren, ob eine Open-Source-Offline-STT-Engine mit einer proprietären Cloud-basierten STT-Engine konkurrieren kann. Zusätzlich sollte eine geeignete STT-Engine oder ein Sprachassistent evaluiert werden. Darüber hinaus wurde eine Analyse der Anpassungsmöglichkeiten der STT-Modelle durchgeführt. Nach der technischen Analyse fiel die Entscheidung zugunsten der STT-Engine namens "Vosk". Auf diese Analyse folgten Versuche, das Modell von Vosk anzupassen. Vosk wurde mit der proprietären Cloud-basierten Google Cloud Speech to Text verglichen, um die Hypothese zu bewerten. Der Vergleich ergab, dass es keinen signifikanten Unterschied zwischen Vosk und Google Cloud Speech to Text gibt. Aufgrund dieses Ergebnisses wurde empfohlen, Vosk für das Exponat zu verwenden. Aufgrund der fehlenden Intent-Parsing-Funktionalität wurden zwei Algorithmen namens "Text-Matching-Algorithmus" und "Text-and-Keyword-Matching-Algorithmus" implementiert und getestet. Dieser Test ergab, dass der Text-and-Keyword-Matching-Algorithmus mit einer durchschnittlichen Erfolgsquote von 83,93 % besser abschnitt. Folglich wurde dieser Algorithmus für das Intent-Parsing des Exponats empfohlen. Abschließend wurden potenzielle Anpassungsmöglichkeiten für die Algorithmen genannt, wie z.B. die Verwendung einer anderen String-Matching-Bibliothek. Es wurden auch einige Verbesserungen bezüglich des Exponats vorgestellt