Search

INTRODUCTION Ocular biometry in Ocular Proton Therapy (OPT) currently relies on a generic geometrical eye model built by referencing surgically implanted markers. An alternative approach based on image fusion of volumetric Magnetic Resonance Imaging (MRI) and panoramic fundus photography was investigated. MATERIALS AND METHODS Eighteen non-consecutive uveal melanoma (UM) patients, who consented for an MRI and had their tumour base visible on panoramic fundus photography, were included in this comparative analysis. Through generating digitally-reconstructed projections from MRI images using the Lambert azimuthal equal-area projection, 2D-3D image fusion between fundus photography and an eye model delineated on MRI scans was achieved and allowed for a novel definition of the target base (MRI + FCTV). MRI + FCTV was compared with MRI-only delineation (MRIGTV) and the conventional (EyePlan) target definition (EPCTV). RESULTS The combined use of fundus photography and MRI to define tumour volumes reduced the average discrepancies by almost 65% with respect to the MRI only tumour definitions when comparing with the conventionally planned EPCTV. With the proposed method, shallow sub-retinal tumour infiltration, otherwise invisible on MRI, can be included in the target volume definition. Moreover, a novel definition of the fovea location improves the accuracy and personalisation of the 3D eye model. CONCLUSION MRI and fundus image fusion overcomes some of the limitations of ophthalmological MRI for tumour volume definition in OPT. This novel eye tumour modelling method might improve treatment planning personalisation, allowing to better anticipate which patients could benefit from prophylactic treatment protocols for radiation induced maculopathy.

Objective. 4D dose reconstruction in proton therapy with pencil beam scanning (PBS) typically relies on a single pre-treatment 4DCT (p4DCT). However, breathing motion during the fractionated treatment can vary considerably in both amplitude and frequency. We present a novel 4D dose reconstruction method combining delivery log files with patient-specific motion models, to account for the dosimetric effect of intra- and inter-fractional breathing variability. Approach. Correlation between an external breathing surrogate and anatomical deformations of the p4DCT is established using principal component analysis. Using motion trajectories of a surface marker acquired during the dose delivery by an optical tracking system, deformable motion fields are retrospectively reconstructed and used to generate time-resolved synthetic 4DCTs (‘5DCTs’) by warping a reference CT. For three abdominal/thoracic patients, treated with respiratory gating and rescanning, example fraction doses were reconstructed using the resulting 5DCTs and delivery log files. The motion model was validated beforehand using leave-one-out cross-validation (LOOCV) with subsequent 4D dose evaluations. Moreover, besides fractional motion, fractional anatomical changes were incorporated as proof of concept. Main results. For motion model validation, the comparison of 4D dose distributions for the original 4DCT and predicted LOOCV resulted in 3%/3 mm gamma pass rates above 96.2%. Prospective gating simulations on the p4DCT can overestimate the target dose coverage V95% by up to 2.1% compared to 4D dose reconstruction based on observed surrogate trajectories. Nevertheless, for the studied clinical cases treated with respiratory-gating and rescanning, an acceptable target coverage was maintained with V95% remaining above 98.8% for all studied fractions. For these gated treatments, larger dosimetric differences occurred due to CT changes than due to breathing variations. Significance. To gain a better estimate of the delivered dose, a retrospective 4D dose reconstruction workflow based on motion data acquired during PBS proton treatments was implemented and validated, thus considering both intra- and inter-fractional motion and anatomy changes., Physics in Medicine and Biology, 68 (11), ISSN:1361-6560, ISSN:0031-9155

PURPOSE Energy changes in Pencil Beam Scanning (PBS) proton therapy can be a limiting factor in delivery time, hence limiting patient throughput and the effectiveness of motion mitigation techniques requiring fast irradiation. In this study, we investigate the feasibility of performing fast and continuous energy modulation within the momentum acceptance of a clinical beamline for proton therapy. METHODS The alternative use of a local beam degrader at the gantry coupling point has been compared with a more common upstream regulation. Focusing on clinically relevant parameters, a complete beam properties characterization has been carried out. In particular, the acquired empirical data allowed to model and parametrize the errors in range and beam current to deliver clinical treatment plans. RESULTS For both options, the local and the upstream degrader, depth-dose curves measured in water for off-momentum beams were only marginally distorted (��(1%,1mm) > 90%) and the errors in the spot position were within the clinical tolerance, even though increasing at the boundaries of the investigated scan range. The impact on the beam size was limited for the upstream degrader while dedicated strategies could be required to tackle the beam broadening through the local degrader. Range correction models were investigated for the upstream regulation. The impaired beam transport required a dedicated strategy for fine range control and compensation of beam intensity losses. Our current parametrization based on empirical data allowed energy modulation within acceptance with range errors (median 0.05 mm) and transmission (median -14%) compatible with clinical operation and remarkably low average 27 ms dead time for small energy changes. The technique, tested for the delivery of a skull glioma treatment, resulted in high gamma pass rates at 1%,1mm compared to conventional deliveries in experimental measurements with about 45% reduction of the energy switching time when regulation could be performed within acceptance. CONCLUSIONS Fast energy modulation within beamline acceptance has potential for clinical applications and, when realized with an upstream degrader, does not require modification in the beamline hardware, therefore being potentially applicable in any running facility. Centers with slow energy switching time can particularly profit from such a technique for reducing dead time during treatment delivery. This article is protected by copyright. All rights reserved.

Background and Purpose: To investigate the impact of organ motion on hypoxia-guided proton therapy treatments for non-small cell lung cancer (NSCLC) patients. Materials and Methods: Hypoxia PET and 4D imaging data of six NSCLC patients were used to simulate hypoxia-guided proton therapy with different motion mitigation strategies including rescanning, breath-hold, respiratory gating and tumour tracking. Motion-induced dose degradation was estimated for treatment plans with dose painting of hypoxic tumour sub-volumes at escalated dose levels. Tumour control probability (TCP) and dosimetry indices were assessed to weigh the clinical benefit of dose escalation and motion mitigation. In addition, the difference in normal tissue complication probability (NTCP) between escalated proton and photon VMAT treatments has been assessed. Results: Motion-induced dose degradation was found for target coverage (CTV V95% up to −4%) and quality of the dose-escalation-by-contour (QRMS up to 6%) as a function of motion amplitude and amount of dose escalation. The TCP benefit coming from dose escalation (+4–13%) outweighs the motion-induced losses (, Radiotherapy & Oncology, 176, ISSN:0167-8140, ISSN:1879-0887

In this article, a predictor–corrector algorithm for the fast polynomial chaos (PC)-based uncertainty quantification (UQ) of multi-walled carbon nanotube (MWCNT) interconnect networks is presented. The proposed algorithm intelligently combines the numerical efficiency of the approximate equivalent single conductor (ESC) model of the MWCNT interconnect network with the rigor and accuracy of a multi-conductor circuit (MCC) model. Consequently, this algorithm significantly accelerates the generation of the PC surrogate models (or metamodels) of the network responses for minimal loss in accuracy. These metamodels can be probed efficiently and repeatedly to quantify the impact of manufacturing and fabrication process uncertainty on the MWCNT network responses.

PurposeUsing a dynamic capabilities lens, this paper aims to study the impact of genomics generally and gene therapy specifically on the rare disease sector of the biopharmaceutical industry.Design/methodology/approachIn this study, 24 genomics-based, rare disease-focused biopharma companies were studied and several variables were tested with respect to enterprise value growth. The companies were analyzed as a group of rare disease firms, as well as by size.FindingsThe authors found that number of employees, revenues, number of pipeline and marketed products and retained earnings are strongly correlated (in that order) with enterprise value in rare disease focused biopharma companies. These correlations seem to be weaker as a company’s market capitalization size decreases, indicating that there tends to be increasing returns to scale.Research limitations/implicationsThis study found that increasing rates of cumulative returns to enterprise value growth depends on accumulating knowledge-based employees and expanding product portfolios of disruptive genomics-based technologies for treating rare diseases. Aggregating skilled and innovative employees (especially in bigger companies) can be seen as a cumulative bolstering factor in leveraging dynamic capabilities which can be recognized, understood and transformed into commercial success (i.e. increasing returns in enterprise value). In other words, technology managers’ job is to manage not only the financial aspects of the technology but also human resources, asset configuration and strategic alliances efficiently toward faster and better innovation. Strong dynamic capabilities can be formed with the accumulation of experience, articulation and codification of knowledge and an adaptive ability to change the way they solve problems as their environment transforms.Originality/valueThis is the first study to demonstrate and measure a relationship between dynamic capabilities and enterprise value in genomics-based rare disease firms. Further, this study highlights the importance of building the capability and capacity to absorb expertise and accumulate knowledge for new product innovations and sustainable competitive advantage in industries characterized by disruptive innovation.

BACKGROUND: Craniospinal irradiation (CSI) is an essential treatment component to achieve cure for some brain tumors in children and young adults/adolescents (C-AYAs). Multimodal treatment approaches are however associated with treatment-related late toxicities in these developing patients. Pencil beam scanning proton therapy (PBSPT) allows for a minimization of dose delivered to organs at risk and the brain integral dose and, thus, potentially also a reduction of radiation-induced adverse events. We report the clinical outcome and toxicity rates after CSI for C-AYAs treated with PBSPT. METHODS: We reviewed 71 C-AYAs with a median age of 7.4 years (1.7 – 21.3) who received CSI with PBSPT. Medullobastoma (n=42, 59%) and ependymoma (n=8, 11%) were the most common histologies. Thirty-four (48%) patients presented with metastatic disease at diagnosis. Sixteen (23%) patients were treated for tumor recurrence/progression and 9 (13%) patients underwent re-irradiation. Median prescribed total dose was 54 GyRBE (18 – 60.4) and median craniospinal dose 24 GyRBE (18 – 36.8). Toxicities were recorded according to CTCAE v5.0. RESULTS: With a median follow-up time of 24 months (2 – 195), 12 (17%) patients died due to progressive disease. Eight (11%) patients experienced local failure and 15 (21%) distant failure after PBSPT. Estimated 2-year OS, LC and DC was 86.9%, 86.0% and 80.4%, respectively. Grade 3 acute toxicity (thrombocytopenia, neutropenia, nausea) was observed in 5 (7%) patients. Late grade 3 toxicities (stroke, cataract and CNS necrosis) were observed in 3 (4%) patients, 8, 9 and 16 months after PBSPT, respectively. One (1%) patient developed grade 4 CNS necrosis 8 months after CSI. Late grade ≥3 toxicity free rate was 92.3% at 2 years. No radiation-induced secondary cancer was observed. CONCLUSION: Excellent tumor and brain/spinal distant control and a low late grade ≥3 toxicity rate after CSI were observed in our cohort of C-AYAs treated with PBSPT.

The response of Al

BackgroundProlonged exposure therapy (PE) is an evidence-based treatment for posttraumatic stress disorder (PTSD) that is underutilized in the military health system. Standard workshop training in PE may not be sufficient to alter provider behavior, but post-workshop consultation requires significant resources. Therefore, it is important to determine the incremental utility of post-workshop consultation.MethodsThis study used a hybrid type III randomized implementation trial at 3 US Army installations. Providers were randomized to receive a 4-day prolonged exposure workshop (Standard training condition,n= 60), or the prolonged exposure workshop followed by 6–8 months of post-workshop expert case consultation (Extended training condition,n= 43). The effects training condition were examined on provider attitudes (self-efficacy in delivering PE, expectations for patient improvement, and beliefs about PE), use of PE and PE components, and clinical outcomes of patients with PTSD (using the Clinician-Administered PTSD Scale (CAPS-5)).ResultsExtended condition providers reported greater improvements in self-efficacy,b= .83, 95% CI [.38, 1.27],t(79) = 3.71,p= .001, andd= .63. A greater proportion of patients in the Extended condition (44%) than in the Standard condition (27%) received at least 1 PE session,b= .76,t(233) = 2.53,p= .012, and OR = 2.13. Extended condition providers used more PE components (M= .9/session) than did Standard condition providers (M= .5/session),b= .54, 95% CI [.15, .93],t(68) = 2.70,p= .007, andd= .68. Finally, decrease in patients’ PTSD symptoms was faster for patients of Extended condition providers than for patients of Standard condition providers,b= − 1.81, 95% CI [− 3.57, − .04],t(263) = − 2.02,p= .045, andd= .66, and their symptoms were lower at the second assessment,b= − 5.47, 95% CI [− 9.30, − 1.63],t(210) = − 2.81,p= .005, andd= .66.ConclusionsPost-workshop consultation improved self-efficacy for delivering PE, greater use of PE, faster PTSD reduction, and lower PTSD severity at the second assessment. To our knowledge, this is the first demonstration that post-workshop case consultation for PE improves patient outcomes.Trial registrationClinicaltrials.gov,NCT02982538. Registered December 5, 2016; retrospectively registered

Highlight • Dosimetric study suggests cognition sparing optimization with PBS-PT > IMRT > VMAT. • If available, PBS-PT is recommended for WV-RT in intracranial germ cell tumors. • IMRT is dosimetrically superior than VMAT regarding neurofunctional OAR sparing., Background Whole-ventricular radiotherapy (WV-RT) followed by a boost to the tumor bed (WV-RT/TB) is recommended for intracranial germ cell tumors (IGCT). As the critical brain areas are mainly in the target volume vicinity, it is unclear if protons indeed substantially spare neurofunctional organs at risk (NOAR). Therefore, a dosimetric comparison study of WV-RT/TB was conducted to assess whether proton or photon radiotherapy achieves better NOAR sparing. Methods Eleven children with GCT received 24 Gy(RBE) WV-RT and a boost up to 40 Gy(RBE) in 25 fractions of 1.6 Gy(RBE) with pencil beam scanning proton therapy (PBS-PT). Intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans were generated for these patients. NOAR were delineated and treatment plans were compared for target volume coverage (TVC), homogeneity index (HI), inhomogeneity coefficient (IC) and (N)OAR sparing. Results TVC was comparable for all three modalities. Compared to IMRT and VMAT, PBS-PT showed statistically significant optimized IC, as well as dose reduction, among others, in mean and integral dose to the: normal brain (−35.2%, −32.7%; −35.2%, −33.0%, respectively), cerebellum (−53.7%, −33.1%; −53.6%, −32.7%) and right temporal lobe (−14.5%, −31.9%; −14.7%, −29.9%). The Willis’ circle was better protected with PBS-PT than IMRT (−7.1%; −7.8%). The left hippocampus sparing was higher with IMRT. Compared to VMAT, the dose to the hippocampi, amygdalae and temporal lobes was significantly decreased in the IMRT plans. Conclusions Dosimetric comparison of WV-RT/TB in IGCT suggests PBS-PT's advantage over photons in conformality and NOAR sparing, whereas IMRT’s superiority over VMAT, thus potentially minimizing long-term sequelae.

High-density materials, such as titanium, used for spinal stabilization, introduces several critical issues in proton therapy (PT). Artefacts affect both contouring and dose calculation. Subsequently, artefacts need to be corrected which is a time-consuming process. Besides, titanium causes proton interactions that are unaccounted for in dose calculation. The result is a suboptimal treatment plan, and indeed decreased local controls have been reported for these patients. Carbon fiber reinforced polyetheretherketone (CFR-PEEK) implant material, which is of low density, potentially solves these issues. For this study, we designed a unique phantom to compare the effects of titanium and CFR-PEEK implants in PT. The phantom contains four interchangeable spinal inserts representing a native spine, and three different spinal stabilizations consisting of titanium only, CFR-PEEK only, and a combination of titanium and CFR-PEEK. All phantom scenarios received the standard treatment workup. Two planning approaches were investigated: a single field plan and a multi-field optimized plan with spinal cord sparing. For both plans we analyzed the following aspects: total volume of artefacts on CT images, time required for artefact correction, effect of planning CT correction on dose calculation, plan robustness to range and set up uncertainties, and finally the discrepancy between the calculated dose and the delivered dose with Gafchromic® film. The CFR-PEEK implant had a 90% reduction of artefacts on CT images and subsequently severely reduced the time for artefact correction with respect to the titanium-only implant. Furthermore, the CFR-PEEK as opposed to titanium did not influence the robustness of the plan. Finally, the titanium implants led to hardware-related discrepancies between the planned and the measured dose while the CFR-PEEK implant showed good agreement. As opposed to titanium, CFR-PEEK has none to minor effects on PT. The use of CFR-PEEK is expected to optimize treatment and possibly improve outcomes for patients that require spinal stabilization.

Purpose/Objective(s) Radiation induced optic neuropathy (RION) is a rare but severe complication of radiotherapy that can lead to visual impairment or blindness. In this retrospective study, we report on RION incidence in a multi-institutional proton therapy cohort (median follow-up - 5.6 years), while determining risk factors that model the probability of this normal tissue complication (NTCP). Materials/Methods 292 chondrosarcoma (65%) and chordoma (35%) patients were included in the study, all treated with proton-only or combined photon-proton regimens at two institutions (50%/50%). Inclusion criteria were adults, absence of chemotherapy and at least 45 GyRBE dose planned to any part of the optic apparatus. Clinical variables and dosimetry were assessed in univariate and multivariate analyses including bootstrapping, cross-validation and stepwise logistic regression, to identify the most robust predictive factors and to develop a RION NTCP model. Results RION incidence grade ≥ 1 (mean 2.9, CTCAE 5.0) was observed in 12 patients (4.1%). Age (P = 0.008), arterial hypertension (P Conclusion Age and hypertension have been confirmed as significant risk factors for RION in a multi-institutional proton therapy cohort of patients receiving more than 45 GyRBE to the optic apparatus. While, in agreement with previous reporting, surgery and tumor abutment of the optic pathway emerged as potentially predictive factors, their statistical power was not sufficient for inclusion into the NTCP model. Author Disclosure A. Kothe: Research Grant; PHRT, ETH Domain. L. Feuvret: None. S. Safai: None. A. Lomax: None. D.C. Weber: None. G. Fattori: None.

This paper aims to study the relevance and importance of strategic alliances for emerging technology adoption. The case researched and discussed here is Blockchain adoption in the semiconductor industry. As a technology, Blockchain has been around for over a decade and is known to provide tremendous value in business transactions. However, the adoption has not gained traction mainly due to the fact that it takes a network to adopt an industrial Blockchain and cannot work in silos. Most companies are shying away from it as they haven't explored what makes a successful strategy for adoption. A literature review was done on the similar technology adoption in the past. The nature of Blockchain and its network dependency were considered. It was clear that strategic alliances are the way to move forward. The various aspects to be considered while forming an alliance, such as understanding the core competencies, finding the right partners, and form of alliances was studied. The research converged in understanding the fact that companies should move away from the transactional business model and have the right expectations and scoping on all sides, standardization, digital integration, and a steady focus on security and privacy.

A study of the online social networks of six Twitter conversations about six YouTube product categories reveals that directionality and network size affect the structure of online social networks. Our results indicate that large networks tend to be non-random, regardless of whether they are directional or not, suggesting that structural attributes of the online networks under study are a true reflection of network's features. Smaller non-directional networks also tend to be non-random, whereas smaller directional networks tend to be random in nature. However, very small networks tend to be random in nature, whether they are directional or not. Our results suggest that larger online networks undergo different generation mechanisms than smaller real-world networks, especially if these networks are directional. Extant theory, which is almost exclusively derived from observation of real-world networks, may thus not adequately describe the behavior of online networks. We propose research to remedy this deficiency at the end of this paper.

In this paper, a predictor-corrector algorithm for the fast stochastic analysis of multi-walled carbon nanotube (MWCNT) interconnect networks is proposed. This algorithm begins by developing a polynomial chaos (PC) predictor metamodel to capture the coarse features in the stochastic network response. In order to expedite the construction of the predictor metamodel, the compact but approximate equivalent single conductor (ESC) model of the network is used. Thereafter, the finer features of the stochastic network response are captured using a corrector metamodel. This corrector metamodel is formulated using a very sparse set of the rigorous and expensive multi-conductor circuit (MCC) model. The combination of the predictor and corrector metamodels is found to be far more efficient than conventional PC metamodels constructed using the MCC model only. In this paper, the scaling of the efficiency factor with respect to the number of shells in the MWCNT network is quantified.

A broadly based, quantitative, empirical study of 208 R&D projects within the national laboratories (NLs) of a technology latecomer country (TLC) finds that the performance of R&D projects within the NLs of that TLC is highly dependent on the pathway by which knowledge enters the R&D project group that delivers the project or on how it is created therein. Performance also depends upon the mission of the NLs with which the project is aligned. These findings suggest that managers of R&D project groups within the NLs in this TLC can take a nuanced approach to organizational learning. They can improve the performance of individual R&D projects by emphasizing the knowledge pathways that have the greatest positive impact on the mission that is most important to the project. The study’s findings also provide theoretical insights that go beyond the context of NLs in TLCs. They explain why vicarious learning cannot be associated positively with team performance, and they suggest that contextual learning is positively correlated to team performance under specific circumstances, only. Moreover, the findings imply that extant theory on organizational learning is insufficiently granular to explain the apparently complex relationship between group knowledge and group performance.

This paper presents an empirically grounded model, which links organizational learning to pattern-specific fixed costs in integrated device manufacturing. The approach described in this paper helps fab managers make fundamental strategic decisions concerning product design and product mix by engaging in scenario planning. Four critical aspects of managing pattern-specific fixed cost are analyzed in detail—sensitivity to time, design cost, and production volume; platform designs; process postponement solutions; and design penalties. The model suggests that designers and fabrication facilities must collaborate extensively on the design and realizations of product platforms for state-of-the-art integrated circuit products to remain economically viable.

Almost one year ago, we sent selected authors who had presented at the SEMI Advanced Semiconductor Manufacturing Conference 2015 the following letter.

Text mining methods allow researchers to investigate technical documents (tech mining) and specifically explore patents for valuable information (patent mining. To the review literature and analyze the evolution of patent analysis and patent mining methods, bibliometrics analysis and keyword-based network analysis is applied on 143 papers extracted from the 'Web of science' database. Bibliometrics analysis was applied to determine top players researching in patent mining. Applying cluster analysis on the keyword network shows three main stages of patent analysis evolution. Also, it is discussed how patent mining is evolutionized in terms of information retrieval, pattern recognition and pattern analysis.

Purpose Four-dimensional computed tomography-magnetic resonance imaging (4DCT-MRI) is an image-processing technique for simulating many 4DCT data sets from a static reference CT and motions extracted from 4DMRI studies performed using either volunteers or patients. In this work, different motion extraction approaches were tested using 6 liver cases, and a detailed comparison between 4DCT-MRI and 4DCT was performed. Methods and Materials 4DCT-MRI has been generated using 2 approaches. The first approach used motion extracted from 4DMRI as being "most similar" to that of 4DCT from the same patient (subject-specific), and the second approach used the most similar motion obtained from a motion library derived from 4DMRI liver studies of 13 healthy volunteers (population-based). The resulting 4DCT-MRI and 4DCTs were compared using scanned proton 4D dose calculations (4DDC). Results Dosimetric analysis showed that 93% ± 8% of points inside the clinical target volume (CTV) agreed between 4DCT and subject-specific 4DCT-MRI (gamma analysis: 3%/3 mm). The population-based approach however showed lower dosimetric agreement with only 79% ± 14% points in the CTV reaching the 3%/3 mm criteria. Conclusions 4D CT-MRI extends the capabilities of motion modeling for dose calculations by accounting for realistic and variable motion patterns, which can be directly employed in clinical research studies. We have found that the subject-specific liver modeling appears more accurate than the population-based approach. The former is particularly interesting for clinical applications, such as improved target delineation and 4D dose reconstruction for patient-specific QA to allow for inter- and/or intra-fractional plan corrections.

Papers addressing the Dynamic Capability (DC) approach either support it as the best strategy or express its defects and impediments to implementation. However, this paper aims to promote the DC through the means of digital transformation from the angle of Business Intelligence and Data Analytics (BIDA). This article employs the logic of matching the essential components of the DC and BIDA to verify the extent of their conformity. A literature review methodology has been adopted since there are a considerable number of publications that focus on DC and BIDA. This paper posits that the main components of DC are sensing and exploring changes, seizing opportunities, and managing reconfiguration and transformation. Whereas, the features of knowledge discovery, decision support, predicting changes and risks are related to the BIDA. Additionally, this study found that the BIDA has a significant positive effect on the DC and helps to achieve a competitive advantage. By drawing the connection and demonstrating the impact of the essential elements of DC and BIDA, this article shows the vital framework of how the BIDA supports the DC. Finally, some limitations and gaps that provide suggestions for future research in this area are discussed.

It has always been assumed that a large conversation about a topic on social media implies that the topic is popular. However, an empirical study of Twitter conversations about a variety of YouTube product categories, which is described in this paper, has shown that this is not necessarily the case. Popularity as measured by distribution volume is not necessarily a reliable indicator of the size of a community or conversation that is associated with a product category. This suggests that current online marketing practices are not nearly as effective as has been assumed to date. Novel, potentially more effective approaches to online marketing are suggested in the paper.

The Libyan cellular market still new, and it is primarily a competition between two major players. Also, there are serious steps inside the Libyan Ministry of Telecommunication to make a real competition inside the market. All those things have motivated the author to write this paper. The author is trying to help the leading players inside the market to know more about the best response that gave them best results. We have applied Game Theory because it is the strategic tool that gives you the best analysis and response when you have a competition between two players. The model that we have used here is Bertrand's model. This model is used when two companies are competing over price. We have noticed from our model analysis and our paper analysis that a price war might happen in this market. Therefore, we came up with recommendations to the regulators to organize the competition. Also, the author lists several recommendations to the operators that help them in case that price war happened in the market.

This research intensively reviews and analyzes the strategic management of technology at Nokia Corporation. Using traditional narrative literature review and secondary sources, we reviewed and analyzed the historical transformation of Nokia's core business, leadership strategies, business architecture, R&D policy, innovation strategy, product lunch, and smartphones recognition and demonstration. We identified various strategic gaps that the previous analytical studies seemingly have missed to identify and generalize. Therefore, we add to the literature a bundle of the lessons learned that chronologically explain how Nokia failed to create and sustain competitive advantages, particularly in the smartphone market. We concluded that the problem at Nokia was not the lack of innovation, but rather, it was the lack of a precise technology forecasting, and misunderstanding that the needs in smartphone market were not just about demonstrating a mobile phone that makes calls, texts and connects to the web, but also the platform that operates all these functions together. Since Nokia's brand name is recently back in the market through a newly licensed firm (HMD Global), we further discuss how likely the new Nokia's smartphones will possibly compete and plausibly succeed in a very well-established market.

The multinational biopharmaceutical industry has to deal with significant financial pressures due to being a very cost-constrained and highly regulated industry. To add to that, finite patent expirations on financially successful drugs, vying nature of the biotech industry due to new innovations. There has been an increase of smaller markets due to the proliferation of molecular segmentation patient populations in fields such as personalized medicine. Particularly, due to the significant cost reducing impacts of the development of "next-generation" sequence platforms on DNA sequencing in the last decade, molecular diagnostics are being considered as cost effective candidates to be used as a standard medical test, in terms of risk assessment, confirmation of diseases, and therapeutics. Biopharmaceutical companies need to reassess their drug development strategies and choose among alternative prospective business models in order to remain relevant amid the new innovations and developments. Using a dynamic capabilities lens, this paper tends to study the impact of genomics generally and gene therapy specifically on the rare disease sector of the biopharmaceutical industry by analyzing the public data from 24 genomics based rare disease focused biopharmaceutical companies. This study shows that growing rates of cumulative returns is dependent upon the accumulation of knowledge-based employees and expanding product portfolios of disruptive genomics-based technologies for treating rare diseases. Further, this study stresses the significance of structuring the capability and capacity to absorb expertise and accrue knowledge for new product innovations and viable competitive advantage.

This research reviews a comprehensive and somehow chronological literature in the models and frameworks of competition and strategy. Strategic management research is shaped around a core question that why some firms outperform others; several significant lines of work have emerged in the strategic management field since its infancy. These include industrial organization, the resource-based view and dynamic capabilities. Also, Competition essentially has been the focal point of scholars with diverse perspectives such as industrial economics and structural analysis, strategic groups, game theory, and competitive dynamics. In this research, we represent and summarize different perspectives of scholars in framing competition and strategy that is related to theory of the firm and differential firm performance; also, we show that there is a trend from static to dynamic frameworks of strategy and competition which have tried to find an answer to differential firm performance. Finally, we conclude by addressing the potential for utilizing new dynamic and systemic perspectives regarding theorizing dynamics of strategy and competition.

Modeling how patients adopt personal health technology is a challenging problem: Decision-making processes are largely unknown, occur in complex, multi-stakeholder settings, and may play out differently for different products and users. To address this problem, this chapter develops a soft analytics approach, based on Fuzzy Cognitive Maps (FCM) that leads to adoption models that are specific for a particular product and group of adopters. Its empirical grounding is provided by a case study, in which a group of women decides whether to adopt a wearable remote healthcare monitoring device. The adoption model can simulate different product configurations and levels of support and provide insight as to what scenarios will most likely lead to successful adoption. The model can be used by product developers and rollout managers to support technology planning decisions.