Cross-Sector Competition in Telecommunications - An Empirical Analysis of Diversification Activities

Cross-sector competition in the information and communications technology sectors (ICT sectors) constitutes a key strategic challenge for telecommunications companies. Due to increasing convergence, value creation is resulting in a greater degree of interaction. The diversification potential of telecommunications businesses is therefore changing with respect to associated ICT sectors, such as hardware, software and media. The article analyses cross-sector competition in the telecommunications industry on the basis of the diversification activities of ICT companies. A concentration of competitive interdependence in the ICT sectors is demonstrated using a cluster analysis of 34,142 companies. The cross-sector activities of telecommunications companies are investigated using contingency and dependency analyses, and the diversification- related competition in the telecommunications sector is also analysed. With regard to the telecommunications sector, particularly high level cross-sector competition with the media industry is identified, as well as strong diversification activities in the software sector. The results are used to derive the potentials and risks that have a significant bearing on the structure of the cross-sector competitive environment of telecommunications companies

A typology of cooperation strategies in the telecommunication industry: An exploratory analysis and theoretical foundations

The value chain of the telecommunication industry is subject to a continuing disintegration which is caused by outsourced network operation, the provisioning of wholesale interfaces to competing service providers and the cooperative provisioning of broadband access. Thus, many companies regard cooperation as an element of cooperate strategy. In this paper we propose a cooperation topology for the telecommunication industry and identify drivers of cooperation based on the assessment of case studies. The results indicate that drivers of cooperation differ with respect to the cooperation direction and that the combination of complementary resources is the dominating driver of cooperation. --Cooperation,telecommunication,typology of cooperation strategies,transaction costs

Transforming Personal Healthcare through Technology - A Systematic Literature Review of Wearable Sensors for Medical Application

Wearable Sensor Health Technology (WSHT) captures, analyzes and aggregates physiological data to improve personal well-being. Recently the technology market is flooded with wearable sensors that measure health-related data and have a high user adoption. Nevertheless, these devices are almost exclusively used for fitness purposes and the healthcare sector still faces the challenge of constantly increasing costs. To respond to the necessary but rare use of WSHT in professional healthcare, we aim to identify the most promising areas for future medical implementation. Therefore, we performed a systematic literature search and reviewed 97 papers with regard to disease treatment, application area, vital parameter measurement and target patient. As a result, we could identify five potential areas for further research: (RA1) concentration on widespread diseases, (RA2) expansion of WSHT’s functionality, (RA3) diversity of vital parameter measurements, (RA4) proactive analysis of sensor data for preventive purposes and (RA5) promoting patient adoption through enhanced usability

A value proposition oriented typology of electronic marketplaces for B2B SaaS applications

In order to overcome the lack of transparency of the SaaS market, electronic marketplaces (EMs) emerge in practice. To the best of our knowledge, only little research has been carried out in this specific domain. As it is of outmost importance to understand the value offerings, the goal of this paper is to develop a typology of EMs considering the value proposition and other differentiating characteristics. An explorative multiple case study approach is employed analyzing 17 cases utilizing publically available data. We propose a five-step-typology, in particular: (1) Catalogue Listing, (2) Transaction-oriented Catalogue, (3) All-in-One Marketplace, (4) Development Platform Marketing Channel and (5) Industry Collaboration Development Platform. In addition, we analyze and discuss the general market situation of EMs for B2B SaaS applications. Based on our findings, we derive implications for practice and identify potential for further research

Towards a Cloud Computing Selection and Evaluation Environment for Very Large Business Applications

Due to their maturity Cloud Computing Services can be used for creating efficient and modern Very Large Business Applications (VLBAs). These kinds of systems address the need for more agility in the whole supply chain with a loosely coupled system of separate cloud computing services combined to a highly integrated, complex Information System. But due to the fast growth of Cloud Computing the market has become non-transparent containing many offers which only partially meet customers’ requirements. That makes it even more difficult for customers to implement Cloud based VLBA-Systems. A detailed knowledge of universal Cloud requirements enables all types of customers to adopt Cloud solutions efficiently. Therefore this paper aims to contribute a framework addressing the adoption and selection of Cloud services for VLBA-Systems. To develop this framework we followed a design science approach and conducted a systematic literature review, extensive market analysis and an evaluation based on expert interviews

The Value of Community Clouds for Collaboration in the Public Sector

The public sector has discovered cloud computing technologies and therefore demands an adequate cloud provisioning model. The community cloud seems to be a good balance between safety and trust as well as efficiency, cost reduction, and competitiveness for public facilities. Following this presumption, we analyzed the network potential for cooperation in the public sector. First, we reviewed the scientific literature around this concept and clarified the term ‘community cloud’. Then, we conducted a study of network theories to derive common values that are addressed in cooperation. In combination with network characteristics, we developed a framework that characterizes a network and assesses its specific network value. For evaluation purposes, we applied the framework to community cloud implementations in the public sector and discussed the results regarding the network value. The research findings reveal basic network values for community clouds in the public sector and will serve as analysis and assessment guidelines

Data Center Green Performance Measurement: State of the Art and Open Research Challenges

Data centers (DC/DCs) are indispensable elements of information systems. The increase in information technology service demand drives their worldwide grow in number, size and energy consumption. In the light of depleting raw natural resources and climate change induced by greenhouse gases (GHG) the environmental impacts of DCs have received particular attention. This paper reviews literature to highlight major issues that contribute to DCs ecologic sustainability, and explores the state of the art of green performance indicators (GPIs) to assess DCs environmental performance, in particular the energy, GHG and resource efficiency. Afterwards, the identified GPIs are classified and clustered to construct a green performance measurement system. Furthermore, the paper generates insights in relation to the recognition and application of proposed GPIs in practice through 13 questionnaires and two expert interviews. Thus, the paper provides academics and practitioners with the body of knowledge on DC green performance measurement, and moreover formulates open research challenges

Security and Privacy System Requirements for Adopting Cloud Computing in Healthcare Data Sharing Scenarios

The emerging cloud computing technology enables new essential scenarios in healthcare, in particular those of data sharing among practitioners. Nevertheless, their security and privacy concerns still impede the wide adoption of cloud computing in this area. Although there are numerous publications in the context of cloud computing in healthcare, we found no consistent typical security and privacy system requirements framework in this domain so far. Owing to the lack of those studies and preparing the ground for creating secure and privacy-friendly cloud architectures for healthcare, we survey security and privacy system requirements for cloud-based medical data sharing scenarios using two strategies. We base on a systematic design science approach following the literature-driven requirement elicitation strategy and apply an established security requirement elicitation methodology as part of the scenario-driven strategy. Finally, we evaluate and compare the two security and privacy system requirements elicitation strategies used in this paper

ACCEPTANCE OF HEALTH CLOUDS - A PRIVACY CALCULUS PERSPECTIVE

The cloud computing paradigm promises to significantly improve the transfer of crucial medical records during medical service delivery. However, since cloud computing technology is still known for unsolved security and privacy challenges, severe concerns could prevent patients and medical workers from accepting such an application scenario. Owing to the lack of similar studies, we investigate what determines an individual´s information privacy concerns on cloud-based transmission of medical records and whether perceived benefits influnce the behavioral intention of individuals to permit medical workers to transfer their medical records via cloud-based services. Based on different established theories, we develop and empirically test a corresponding research model by a survey with more than 260 full responses. \ \ Our results show the perceived benefits of this health cloud scenario override the impact of information privacy concerns even in the privacy-sensitive German-speaking area and immediately after the NSA scandal. Somewhat surprisingly, we also find that in this scenario knowledge about information privacy has no significant effect on information privacy concerns although some relations have been observed in previous empirical studies. Finally, patient information privacy concerns can be mitigated by establishing trust in cloud providers in healthcare as well as in privacy-preserving technological and regulatory mechanisms

Employing Environmental Data and Machine Learning to Improve Mobile Health Receptivity

Behavioral intervention strategies can be enhanced by recognizing human activities using eHealth technologies. As we find after a thorough literature review, activity spotting and added insights may be used to detect daily routines inferring receptivity for mobile notifications similar to just-in-time support. Towards this end, this work develops a model, using machine learning, to analyze the motivation of digital mental health users that answer self-assessment questions in their everyday lives through an intelligent mobile application. A uniform and extensible sequence prediction model combining environmental data with everyday activities has been created and validated for proof of concept through an experiment. We find that the reported receptivity is not sequentially predictable on its own, the mean error and standard deviation are only slightly below by-chance comparison. Nevertheless, predicting the upcoming activity shows to cover about 39% of the day (up to 58% in the best case) and can be linked to user individual intervention preferences to indirectly find an opportune moment of receptivity. Therefore, we introduce an application comprising the influences of sensor data on activities and intervention thresholds, as well as allowing for preferred events on a weekly basis. As a result of combining those multiple approaches, promising avenues for innovative behavioral assessments are possible. Identifying and segmenting the appropriate set of activities is key. Consequently, deliberate and thoughtful design lays the foundation for further development within research projects by extending the activity weighting process or introducing a model reinforcement.BMBF, 13GW0157A, Verbundprojekt: Self-administered Psycho-TherApy-SystemS (SELFPASS) - Teilvorhaben: Data Analytics and Prescription for SELFPASSTU Berlin, Open-Access-Mittel - 201