Customer-driven innovation within U.S. business services and its impact on firm performance

This thesis examines the innovative performance of 206 U.S. business service firms. Undeniably, a need exists for better comprehension of the service sector of developed economies. This research takes a unique view by applying a synthesis approach to studying innovation and attempts to build under a proposed strategic innovation paradigm. A quantitative method is utilised via questionnaire in which all major types of innovation are under examination including: product and service, organisational, and technology-driven innovations. Essential ideas for this conceptual framework encapsulate a new mode of understanding service innovation. Basically, the structure of this analysis encompasses the likelihood of innovation and determining the extent of innovation, while also attempting to shed light on the factors which determine the impact of innovation on performance among service firms. What differentiates this research is its focus on customer-driven service firms in addition to other external linkages. A synopsis of the findings suggest that external linkages, particularly with customers, suppliers and strategic alliances or joint ventures, significantly affect innovation performance with regard to the introduction of new services. Service firms which incorporate formal and informal R&D experience significant increases in the extent of new-to-market and new-to-firm innovations. Additionally, the results show that customer-driven service firms experience greater productivity and growth. Furthermore, the findings suggest that external linkages assist service firm performance

Coronavirus disease 2019 (COVID-19): A New Pandemic and its Challenges

Emerging of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide outbreak and a major public health problem. The present review was conducted to provide brief information about the origin, symptoms, transmission, pathogenesis, diagnosis, and treatment of the virus. A search was performed in the databases of PubMed, Scopus, Science Direct, and Google scholar with English keywords including 2019-nCoV, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, and novel coronavirus from December 2019 to 15 March 2020, and the search results were evaluated. Selected studies have shown that the virus may have originated from the bat. It has also been shown that the virus receptor is angiotensin-converting enzyme 2 (ACE2) which is also the SARS virus receptor and is expressed in most human tissues. The most common way of virus transmission was suggested through respiratory droplets and close contact. It is also transmitted by asymptomatic patients, but vertical transmission from mother to fetus has not been confirmed. Real-time reverse transcriptase (RT)-PCR is the gold standard for SARS-CoV-2 detection, but chest computed tomography (CT) can be more sensitive to detect positive cases. Since no effective vaccine or drug for prevention and treatment of this disease has not yet been identified and also because of the high incubation and infection period, easy transmission, and the lack of complete recognition of the characteristics and stability in different environments, the best way to control of COVID-19 is to prevent the spread of the infection in different ways and take seriously personal and public hygiene

Emerging Spatiotemporal Patterns from Discrete Migration Dynamics of Heterogeneous Agents

We propose a discrete agent-based model to investigate the migration dynamics of heterogeneous individuals. Compatibility among agents of different types is expressed in terms of homophily parameters capturing the extent to which similar individuals are attracted to, or dissimilar individuals are repelled by, each other. Based on agent-based simulations, we establish the connection between emerging spatiotemporal patterns and the homophily parameters. Key results are presented in a novel phase diagram, which reveals a wide range of spatial patterns including the cell, worm, herd, amoeba, and swarm modes under the dynamic regime and the separation, ghetto, and integration modes under the stationary one. Our model thus provides a generalized framework encompassing both static equilibrium and nonstationary systems to investigate the impact of agent heterogeneity on population dynamics. We demonstrate potential applications of our model to social systems using sexual segregation of ungulate habitats as a case study

Exporting and productivity in business services:evidence from the United States

Does exporting make firms more productive, or do more productive firms choose to become exporters? This paper considers the link between exporting and productivity for a sample of firms in US business services. We find that larger, more productive firms are more likely to become exporters, but that these factors do not necessarily influence the extent of exporting. This conforms with previous literature that there is a self-selection effect into exporting. We then test for the effect of exporting on productivity levels after allowing for this selection effect. We model both the relationship between exporting and productivity, and a simultaneous relationship between export intensity and productivity after allowing for selection bias. In both cases we find an association, indicating that productivity is positively linked both to exporting and to increased exposure to international markets

A Growth Model for Multicellular Tumor Spheroids

Most organisms grow according to simple laws, which in principle can be derived from energy conservation and scaling arguments, critically dependent on the relation between the metabolic rate B of energy flow and the organism mass m. Although this relation is generally recognized to be of the form B(m) = mp, the specific value of the exponent p is the object of an ongoing debate, with many mechanisms being postulated to support different predictions. We propose that multicellular tumor spheroids provide an ideal experimental model system for testing these allometric growth theories, especially under controlled conditions of malnourishment and applied mechanical stress

Model Replication in the Context of Agent-Based Simulation: Lessons Learnt from Two Case Studies

This paper examines model replication in the context of agent-based simulation through two case studies. Replication of a computational model and validation of its results is an essential tool for scientific researchers, but it is rarely used by modelers. In our work we address the question of validating and verifying simulations in general, and summarize our experience in approaching different models through replication with different motivations. Two models are discussed in details. The first one is an agent-based spatial adaptation of a numerical model, while the second experiment addresses the exact replication of an existing economic model

Validating an agent-based model of the Zipf׳s Law: A discrete Markov-chain approach

AbstractThis study discusses the validation of an agent-based model of emergent city systems with heterogeneous agents. To this end, it proposes a simplified version of the original agent-based model and subjects it to mathematical analysis. The proposed model is transformed into an analytically tractable discrete Markov model, and its city size distribution is examined. Its discrete nature allows the Markov model to be used to validate the algorithms of computational agent-based models. We show that the Markov chains lead to a power-law distribution when the ranges of migration options are randomly distributed across the agent population. We also identify sufficient conditions under which the Markov chains produce the Zipf׳s Law, which has never been done within a discrete framework. The conditions under which our simplified model yields the Zipf׳s Law are in agreement with, and thus validate, the configurations of the original heterogeneous agent-based model

Inverse Geometric Approach to the Simulation of the Circular Growth. The Case of Multicellular Tumor Spheroids

We demonstrate the power of the genetic algorithms to construct the cellular automata model simulating the growth of 2-dimensional close-to-circular clusters revealing the desired properties, such as the growth rate and, at the same time, the fractal behavior of their contours. The possible application of the approach in the field of tumor modeling is outlined