Internet Marketing for Profit Organizations: A framework for the implementation of strategic internet marketing

Merged with duplicate record 10026.1/828 on 13.03.2017 by CS (TIS)The development of the Internet has significantly changed the face of established markets and operation approaches across a tremendous spectrum of different industries. Within the competitive environment of those industries, the opportunities and risks derived from the new platform are so ubiquitous that unused opportunities quickly translate into potential risks. Those opportunities and risks demand for a structured approach how to implement a sustainable Internet marketing strategy that targets clear business objectives. Marketing and strategic management theory describes very clear structural principles towards their operational implementation. Based on those principles an extensive literature review has been conducted which confirms the result from representative statistics that demonstrate the lack of a comprehensive framework for strategic Internet marketing. The distinct result of this research is such a comprehensive framework which has been directly derived from the illustrated principles of strategic management and Internet marketing. All major components of this generic framework are designed, evaluated in dedicated surveys and validated in extensive case studies. The main achievements of the research are: • A comprehensive review of the current state-of-the-art Internet marketing strategies • Conceptual specification of a strategic Internet marketing framework with generic applicability to profit organizations • Demonstration of the practical feasibility of the proposed framework at the implementation level (via several examples like the SIMTF and SIMPF) • Confirmation of the applicability of the framework based upon a survey of potential beneficiaries • Validation of the effectiveness of the approach via case study scenarios Changing the understanding of a former technical discipline, the thesis describes how Internet marketing becomes a precise strategic instrument for profit organizations. The new structured, complete and self-similar framework facilitates sales organizations to significantly increase the effectiveness and efficiency of their marketing operations. Furthermore, the framework ensures a high level of transparency about the impact and benefit of individual activities. The new model explicitly answers concerns and problems raised and documented in existing research and accommodate for the current limitations of strategic Internet marketing. The framework allows evaluating existing as well as future Internet marketing tactics and provides a reference model for all other definitions of objectives, KPI and work packages. Finally this thesis also matures the subject matter of Internet marketing as a discipline of independent scientific research providing an underlying structure for subsequent studies.Darmstadt Node of the CSCAN Network at University of Applied Sciences, Darmstad

The Relationship Between Hospitals’ Electronic Health Records Maturity and Excess Readmission Ratio

Since the Health Information Technology for Economic and Clinical Health Act was enacted in 2009, a majority of U.S. hospitals have adopted electronic health records (EHR) to improve quality of care. However, variations exist in the technology\u27s capability and maturity, making it difficult for researchers to analyze the full impact. The purpose of this quantitative study was to explore the relationship between hospitals\u27 EHR maturity and the quality measure of excess readmissions, as well as the relationship between hospital characteristics, specifically, hospital location and the number of licensed beds in Medicare hospitals (N = 1,006). Both the chi-square statistical test and logistic regression models were used to analyze whether EHR maturity has an impact on excess readmissions. Rogers\u27s diffusion of innovation provided the theoretical framework. A retrospective data analysis for FY 2017 was conducted using EHR adoption analytics from the Healthcare Information and Management Systems Society and excess readmission ratio (ERR) data from the Centers for Medicare and Medicaid Services’ Hospital Readmissions Reduction Program. Analyses indicated no significant association between EHR maturity and ERR for either coronary artery bypass grafts or total hip or total knee arthroplasty (THA/TKA). However, there was a significant relationship between hospitals\u27 EHR maturity, location, and number of licensed beds. In addition, EHR maturity and hospitals\u27 location were significant predictors of elective primary THA/TKA ERR. The results of this study may lead to positive social change by informing hospital administrators on the impact of investments in mature EHR technology to reduce excess readmissions and improve quality of care

Maturing maturity models: A methodological extension using the analytical hierarchy process and Google PageRank

Maturity models are used in various application domains, as they provide well-structured overviews about companies’ as-is situations in a certain discipline due to applying different stages of development. However, maturity models face criticism. Most maturity models structure only their respective field of activity without adding value for decision-making purposes. There is a lack of models for prescriptive purposes that help derive and balance concrete improvement measures. In addition, maturity models are criticised for oversimplifying reality. To address this gap, we propose a methodological extension to enhance maturity models, such that they explicitly account for the importance of multiple capability areas and consider the impact of the interactions among capability areas. To do so, we combine methods from multi-criteria decision-making, that is, the error-adjusted Analytical Hierarchy Process, and from network analytics, that is, the Google PageRank

Scottish space sector and innovation: a PERIpatetic study of an emerging innovation system and the roles of innovation intermediaries

This thesis seeks a more effective understanding of Open Innovation (OI) and the available strategies for its development within (geographically–bound) sectoral systems of innovation (GSSIs). Theoretically, it draws upon the competing intellectual traditions (from innovation studies and from science and technology studies) with their different presumptions, which alternatively favour either macro-level positivist or micro-level interpretativist perspectives. These divides prevent a more holistic theoretical understanding of OI, and present a challenge to practitioners, who struggle to operationalise the theories’ insights. Hence, this thesis proposes a novel Practical Epistemology for Researching Innovation, i.e. the PERIpatetic Approach, which aims to integrate multiple theoretical and empirical perspectives for a flexible, problem-driven academic enquiry. This new framework for participatory action research is based on “abductive” theory development, which uses bottom-up empirical engagement to identify emergent challenges to state-of-the-art understanding. The research methodology put forward for this approach is centred on strategic ethnography of innovation, which combines multi-sited mixed-method research design, with constructive embeddedness in the field. The empirical focus of this thesis is on the emergence of the (New) Space Sector in Scotland - mainly made up of small-to-medium-sized enterprises (SMEs). Here, miniaturisation and cheapening of core technologies and increased access to space data has been driving significant sectoral growth and diversification – which is of interest to entrepreneurs and politicians alike. I approached the field by being embedded within an active intermediary, which wanted to understand and respond to these trends and opportunities. Consequently, this thesis analyses the modelling of OI between macro-level trends and micro-level practices, through a focus on the activities and organisational behaviour of a network of SMEs and opportunities to support them through the work of innovation intermediaries. In its first part, the thesis analyses the UK/Scottish innovation policy in the Space Sector, exposing the dispersion of public investment, which is creating divergent clusters. These clusters attempt to integrate through the concept of “Agile Space” into a collaborative “Living Laboratory”, constructing new markets and developing products. Applying social network analysis and outlining a new concept of innovation moments, I focus on the structures at play within this integrative framing, identifying processes of organisational learning which develop structural absorptive capacity. Thus, I form an integrated multi-level perspective on a (geographically–bound) sectoral system of innovation (MLP-GSSI), which can be applied to other OI contexts and can be adapted for analysing other aspects of complex innovation systems. In the thesis’ second part, the analysis seeks to redress the lack of systemic understanding of the central role of innovation intermediaries, by developing new classification and prototypology of their interventions. To validate and operationalise this new model, I apply it to the network of innovation intermediaries in the Scottish (New) Space Sector. I further contextualise this insight through a detailed case study of two large investments in innovation intermediation in similarly positioned Space Sectors - examining the tension between business development and R&D support for OI-driven smart specialisation

Recent Advances in Social Data and Artificial Intelligence 2019

The importance and usefulness of subjects and topics involving social data and artificial intelligence are becoming widely recognized. This book contains invited review, expository, and original research articles dealing with, and presenting state-of-the-art accounts pf, the recent advances in the subjects of social data and artificial intelligence, and potentially their links to Cyberspace

Computational Methods for Interactive and Explorative Study Design and Integration of High-throughput Biological Data

The increase in the use of high-throughput methods to gain insights into biological systems has come with new challenges. Genomics, transcriptomics, proteomics, and metabolomics lead to a massive amount of data and metadata. While this wealth of information has resulted in many scientific discoveries, new strategies are needed to cope with the ever-growing variety and volume of metadata. Despite efforts to standardize the collection of study metadata, many experiments cannot be reproduced or replicated. One reason for this is the difficulty to provide the necessary metadata. The large sample sizes that modern omics experiments enable, also make it increasingly complicated for scientists to keep track of every sample and the needed annotations. The many data transformations that are often needed to normalize and analyze omics data require a further collection of all parameters and tools involved. A second possible cause is missing knowledge about statistical design of studies, both related to study factors as well as the required sample size to make significant discoveries. In this thesis, we develop a multi-tier model for experimental design and a portlet for interactive web-based study design. Through the input of experimental factors and the number of replicates, users can easily create large, factorial experimental designs. Changes or additional metadata can be quickly uploaded via user-defined spreadsheets including sample identifiers. In order to comply with existing standards and provide users with a quick way to import existing studies, we provide full interoperability with the ISA-Tab format. We show that both data model and portlet are easily extensible to create additional tiers of samples annotated with technology-specific metadata. We tackle the problem of unwieldy experimental designs by creating an aggregation graph. Based on our multi-tier experimental design model, similar samples, their sources, and analytes are summarized, creating an interactive summary graph that focuses on study factors and replicates. Thus, we give researchers a quick overview of sample sizes and the aim of different studies. This graph can be included in our portlets or used as a stand alone application and is compatible with the ISA-Tab format. We show that this approach can be used to explore the quality of publicly available experimental designs and metadata annotation. The third part of this thesis contributes to a more statistically sound experiment planning for differential gene expression experiments. We integrate two tools for the prediction of statistical power and sample size estimation into our portal. This integration enables the use of existing data, in order to arrive at more accurate calculation for sample variability. Additionally, the statistical power of existing experimental designs of certain sample sizes can be analyzed. All results and parameters are stored and can be used for later comparison. Even perfectly planned and annotated experiments cannot eliminate human error. Based on our model we develop an automated workflow for microarray quality control, enabling users to inspect the quality of normalization and cluster samples by study factor levels. We import a publicly available microarray dataset to assess our contributions to reproducibility and explore alternative analysis methods based on statistical power analysis