High Degree Of Personalization Research Articles

Understanding customers’ choice for digital D2C versus multi-brand operations

In recent years, the emergence of highly successful digital multi-brand retailers has facilitated an omnichannel distribution strategy to become the norm for brands. Rather than relying solely on these multi-brand retailers, it is necessary for companies’ omnichannel strategy to establish strong brand-owned direct-to-consumer (D2C) webstores. To help D2C brands make decisions regarding distribution channel choices, this paper investigates the circumstances under which customers prefer brands’ D2C webstores over digital multi-brand retailers and how these circumstances vary across phases of the customer journey. The results from an extensive experimental study demonstrate that, depending on the customer journey, brands’ D2C webstores can compete with digital multi-brand retailers, particularly in product categories characterized by deep assortments, the need for extensive product information, exclusive products, or a high degree of personalization.

ВОЗМОЖНОСТИ И ПРОБЛЕМЫ РОБОТИЗАЦИИ

The increase in labor costs, the shortage of qualified employees, the reduction in the cost of acquiring advanced technologies and the need to find technical solutions to increase competitiveness and strengthen the market position of companies leads to the fact that automation and robotization have become considered by entrepreneurs as business strategies. Opportunities to compete in international markets due only to cheap labor will soon disappear, so the dynamics of global demand for robots and other components of industrial automation in the next few years will remain in double digits. The unemployment rate and the aging of the population are already causing difficulties in finding workers. In some cases, the small scale of production, the wide variety of assortment and the simplicity of the products produced lead to the fact that automation of technological chains does not have sufficient economic justification. However, robotization should not be associated exclusively with mass monotonous production. It can be successfully used in the production of even single products, with a high degree of personalization and higher quality. Mental barriers are a significant obstacle to making a decision on the robotization of production. The article focuses on modern technological changes, as well as the identification of positive and negative consequences of the robotization of the economy.

ПОЗИЦИОНИРОВАНИЕ WHATSAPP И TELEGRAM В КАЗАХСТАНЕ КАК ГРУППОВЫХ ФЕНОМЕНОВ ИНТЕРНЕТ-ПРОСТРАНСТВА

The article analyzes the modern processes of development of Internet messengers (IM), which are defined as a special type of social network. The purpose of the study is to outline the problems of classification and typologization of new types of media resources based on foreign and domestic experience. Examples of complex studies are given, taking into account the technical and target characteristics of mobile and web applications, as well as the administrative policy of their developers about effective security, encryption and data storage. A comparative analysis of the most widespread Internet messengers and social networks in Kazakhstan and their relationship with traditional media is carried out. The statistics of their use and the outlined trends of evolutionary development allowed to identify patterns of distribution on a regional scale against the background of global trends. Empirical data based on the example of mass media of the Kostanay region are presented, giving an idea of the general orientation of editorial policies in the period of formation of the new Internet infrastructure. Special attention is paid to the communication advantages of the leading Internet messengers WhatsApp and Telegram, and their competition with traditional social networks through the introduction and establishment of new information tools (channels, infobots, communities, private groups, etc.). The scientific novelty of the paper lies in the study and detailed analysis of the distinctive features of the new generation of Internet communicators as opposed to web-oriented traditional social networks, identifying the regularity of the ongoing processes and formulating an innovative approach to studying the nature of WhatsApp and Telegram Internet messengers as personal-oriented applications with a high degree of personalization and protection. From a practical point of view, data on the prevalence of IM used in Kazakhstan in comparison with the world experience is given, and the peculiarities of positioning of these means of communication in the Kazakhstani media environment are revealed

Research Progress of 316L Stainless Steel Forming Process based on Selective Laser Melting Technology

Abstract: SLM technology has the advantages of high material utilization, a short processing cycle and a high degree of personalization. 316L stainless steel is widely used in many industrial fields for its excellent various properties. Formed parts made of 316L stainless steel by SLM technology have expanded the application prospects of 316L stainless steel. The article reviews the research progress of the forming process of SLM-formed 316L stainless steel. This paper mainly collates and classifies the research progress and main methods of powder making, processing and forming and post-treatment of 316L stainless steel in the SLM manufacturing process; it summarizes the influence of SLM process parameters on the forming quality and performance of 316L stainless steel. The 316L stainless steel parts formed by SLM have excellent various properties and are widely used in many industrial fields, playing an extremely important role in the development and construction of the country. Although the current SLM forming technology of 316L stainless steel cannot completely replace the traditional machining method, its advantages of "personalized manufacturing" are still the focus of future research in the field of mechanical engineering. With the future progress of science and technology, SLM technology in the field of 316L stainless steel parts forming and manufacturing will be further improved and developed, which will promote SLM technology to better meet the needs of the petrochemical, transportation, aerospace, nuclear industry and food and medical industry applications.

Development of information and communication technologies to study consumer behavior in the process of brand management

This paper investigates tendencies in the development of information and communication technologies for studying consumer behavior in the process of brand management. Trends in consumer behavior have been identified – strengthening environmental awareness and ethics, spreading e-commerce, increasing mobile experience, strengthening the role of personification, etc. The influence of changes in consumer behavior on the process of positioning and promotion of brands was substantiated. The expectations and actions of consumers and directions of the process of brand management as a result of transformation of consumption were characterized. Attention is focused on the role played by information and communication technologies in the study of consumer behavior in the process of brand management. The basic tools by types of information and communication technologies were systematized. It was determined that the main type of information and communication technologies, due to which a high degree of personalization is ensured, are social networks. In addition, technologies for analyzing web data, e-mail, mobile device data were used to study consumer behavior. A three-dimensional model of studying consumer behavior in the process of brand management has been proposed, which takes into account the components of consumer behavior, which needs to be investigated, the stage of the brand's life cycle, technologies for studying consumer behavior. A matrix of choice of appropriate information and communication technologies for studying consumer behavior at different stages of the brand life cycle has been formed. The practical use of the proposed methodological approach will provide more reliable information on various components of consumer behavior. This could create prerequisites for developing an effective strategy for positioning and brand promotion

Characterization and Validation of a New 3D Printing Ink for Reducing Therapeutic Gap in Pediatrics through Individualized Medicines.

3D printing technology can be used to develop individualized medicines in hospitals and pharmacies, allowing a high degree of personalization and the possibility to adjust the dose of the API based on the quantity of material extruded. The main goal of incorporating this technology is to have a stock of API-load print cartridges that could be used at different storage times and for different patients. However, it is necessary to study the extrudability, stability, and buildability of these print cartridges during storage time. A paste-like formulation containing hydrochlorothiazide as a model drug was prepared and distributed in five print cartridges, each of which was studied for different storage times (0 h-72 h) and conditions, for repeated use on different days. For each print cartridge, an extrudability analysis was performed, and subsequently, 100 unit forms of 10 mg hydrochlorothiazide were printed. Finally, various dosage units containing different doses were printed, taking into account the optimized printing parameters based on the results of the extrudability analysis carried out previously. An appropriate methodology for the rapid development of appropriate SSE 3DP inks for pediatrics was established and evaluated. The extrudability analysis and several parameters allowed the detection of changes in the mechanical behavior of the printing inks, the pressure interval of the steady flow, and the selection of the volume of ink to be extruded to obtain each of the required doses. The print cartridges were stable for up to 72 h after processing, and orodispersible printlets containing 6 mg to 24 mg of hydrochlorothiazide can be produced using the same print cartridge and during the same printing process with guaranteed content and chemical stability. The proposed workflow for the development of new printing inks containing APIs will allow the optimization of feedstock material and human resources in pharmacy or hospital pharmacy services, thus speeding up their development and reducing costs.

Implications of AI-based robo-advisory for private banking investment advisory

PurposeAI-based robo-advisory (RA) represents a FinTech application that is already replacing retail investment advisors. In private banking (PB), clients also increasingly expect service provision across different digital channels, but with a higher degree of personalization. Hence, the present study investigates the impact of intelligent RA on the PB investment advisory process to derive both process (re)design knowledge and strategic guidance for artificial intelligence (AI) usage for PB investment advisory.Design/methodology/approachThe present study applies an AI process impact analysis approach by decomposing AI-based RA into three AI application types: conversational agent, customer segmentation and predictive analytics. The analysis results along a reference PB investment advisory process reveal sub-process transformations which are applied for process redesign integrating AI.FindingsThe study results imply that AI systems (1) enable seamless client journeys, (2) increase advisor flexibility, (3) support the client–advisor relationship by applying an omnichannel approach and (4) demand advisor skills to be augmented with technical and statistical knowledge.Originality/valueThe research study contributes (1) an AI process impact analysis approach, (2) derives process (re)design knowledge for AI deployment and (3) develops strategic guidance for AI usage in PB investment advisory.

Model enhanced reinforcement learning to enable precision dosing: A theoretical case study with dosing of propofol.

Extending the potential of precision dosing requires evaluating methodologies offering more flexibility and higher degree of personalization. Reinforcement learning (RL) holds promise in its ability to integrate multidimensional data in an adaptive process built toward efficient decision making centered on sustainable value creation. For general anesthesia in intensive care units, RL is applied and automatically adjusts dosing through monitoring of patient's consciousness. We further explore the problem of optimal control of anesthesia with propofol by combining RL with state-of-the-art tools used to inform dosing in drug development. In particular, we used pharmacokinetic-pharmacodynamic (PK-PD) modeling as a simulation engine to generate experience from dosing scenarios, which cannot be tested experimentally. Through simulations, we show that, when learning from retrospective trial data, more than 100 patients are needed to reach an accuracy within the range of what is achieved with a standard dosing solution. However, embedding a model of drug effect within the RL algorithm improves accuracy by reducing errors to target by 90% through learning to take dosing actions maximizing long-term benefit. Data residual variability impacts accuracy while the algorithm efficiently coped with up to 50% interindividual variability in the PK and 25% in the PD model's parameters. We illustrate how extending the state definition of the RL agent with meaningful variables is key to achieve high accuracy of optimal dosing policy. These results suggest that RL constitutes an attractive approach for precision dosing when rich data are available or when complemented with synthetic data from model-based tools used in model-informed drug development.

Personalizing over-the-counter hearing aids using pairwise comparisons.

Over-the-counter hearing aids enable more affordable and accessible hearing health care by shifting the burden of configuring the device from trained audiologists to end-users. A critical challenge is to provide users with an easy-to-use method for personalizing the many parameters which control sound amplification based on their preferences. This paper presents a novel approach to fitting hearing aids that provides a higher degree of personalization than existing methods by using user feedback more efficiently. Our approach divides the fitting problem into two parts. First, we discretize an initial 24-dimensional space of possible configurations into a small number of presets. Presets are constructed to ensure that they can meet the hearing needs of a large fraction of Americans with mild-to-moderate hearing loss. Then, an online agent learns the best preset by asking a sequence of pairwise comparisons. This learning problem is an instance of the multi-armed bandit problem. We performed a 35-user study to understand the factors that affect user preferences and evaluate the efficacy of multi-armed bandit algorithms. Most notably, we identified a new relationship between a user's preference and presets: a user's preference can be represented as one or more preference points in the initial configuration space with stronger preferences expressed for nearby presets (as measured by the Euclidean distance). Based on this observation, we have developed a Two-Phase Personalizing algorithm that significantly reduces the number of comparisons required to identify a user's preferred preset. Simulation results indicate that the proposed algorithm can find the best configuration with a median of 25 comparisons, reducing by half the comparisons required by the best baseline. These results indicate that it is feasible to configure over-the-counter hearing aids using a small number of pairwise comparisons without the help of professionals.

Fatigue behavior of biomedical Co–Cr–Mo–W alloy fabricated by selective laser melting

Co–Cr–Mo based alloy was widely used biomaterials for metallic implants fields. Recently, selective lase melting (SLM), one of the additive manufacturing technologies, is broadly studied because it can produce metallic implants with complex geometries and high degree of personalization. However, the possibility of mechanical failure must be avoided during the working period of SLM produced biomaterials. Therefore, in this paper we investigated the fatigue behaviors of the SLM Co–Cr–Mo–W alloy and their corresponding microstructure and fracture morphology. The sand mold casting fabricated (Cast) Co–Cr–Mo–W alloys with the same chemical composition as SLM specimens were also investigated and compared. The results showed that the SLM Co–Cr–Mo–W alloy exhibits higher fatigue life, tensile strength, and ductility than Cast Co–Cr–Mo–W alloy. The high fraction of Σ3 boundaries and precipitates in SLM Co–Cr–Mo–W alloy lead to secondary cracks and deflected fatigue crack path, which can alleviate the stress concentrations of the main fatigue cracks and decrease the fatigue crack growth rate. However, the dendritic structure of Cast Co–Cr–Mo–W alloy cause cleavage fracture mode and the large island-like precipitates can generate stress concentration, which result in lower fatigue life. We believed that the results of this work can provide a new perspective towards microstructure regulation for additive manufacturing technology and paved way for in-depth application of SLM fabricated biomedical alloy.

Using 3D Scanning Techniques in Orthopedic Systems Modeling

Abstract Designing orthopedic implants with a long lifespan is essential for improving patients’ quality of life. It is necessary to develop new products with a high degree of personalization for the human body. Physicians and engineers analyzed the geometry and behavior of healthy joints’ motion under specific load conditions as well as the behavior over time and lifetime of orthopedic implants fitted to patients to improve their quality. The paper presents the way in which three-dimensional modeling techniques using specialized software (Catia, SolidWorks) can be combined with reverse engineering techniques (3D scanning) to optimize the design of orthopedic implants. The design of an implant consists of its three-dimensional modeling, as well as simulation of its integration into the human body, in order to analyze its behavior during motion. Therefore, it is necessary not only to 3D model the parts that make up the implant itself, but also to 3D model the bone to which the implant will be fitted. The paper highlights the complementarity of the classic modeling techniques with the reverse engineering techniques, which is necessary because the design of the parts that make up the implant itself can be achieved by specialized software modeling techniques, while the bones, having complex geometries, are better suited to 3D Modeling by scanning.

Biomedical Co-Cr-Mo Components Produced by Direct Metal Laser Sintering

Direct Metal Laser Sintering (DMLS) is an additive manufacturing technique based on a laser power source that sinters powdered materials using a 3D CAD model. The mechanical components produced by this procedure typically show higher residual porosity and poorer mechanical properties than those obtained by traditional manufacturing techniques. In this study, samples were produced by DMLS starting from a Co-Cr-Mo powder (in the γ phase) with a composition suitable for biomedical applications. Samples were submitted to hardness measurements and structural characterization. The samples showed a hardness value remarkably higher that those commonly obtained for the same cast or wrought alloys. In fact, the HRC value measured for the samples is 47 HRC, while the usual range for CAST Co-Cr-Mo is from 25 to 35 HRC. The samples microstructure was investigated by X-ray diffraction (XRD), electron microscopy (SEM and TEM) and energy dispersive microanalysis (EDX) in order to clarify the origin of this unexpected result. The laser treatment induced a melting of the metallic Co-Cr-Mo powder, generating a phase transformation from the γ (fcc) to the ɛ (hcp) phase. The rapid cooling of the melted powder produced the formation of ɛ (hcp) nano-lamellae inside the γ (fcc) phase. The nano-lamellae formed an intricate network responsible for the measured hardness increase. The results suggest possible innovative applications of the DMLS technique to the production of mechanical parts in the medical and dental fields, where a high degree of personalization is required.

Constructing and Deconstructing Gender in Second Life

Digital games are cultural representations that convey the gender system. The narratives of gender that have shaped the gaming industry since the 1980s were influenced by gender stereotypes. The representation of the female, although based on stereotypes, has evolved hand in hand with the representation of women in other media. But what happens when players are given the opportunity to develop their digital representatives? Virtual worlds are among the online games that allow a higher degree of personalization of the avatar and, in order to contribute to a better understanding of how gender identities are being performed within these environments, this paper will present a case study of Second Life. A qualitative methodology was used based on netnographic research. The data collection methods included participant observation and auto-netnography. The researchers would like to propose that to examine how gender is represented in games that enable the creation of the avatar allows to deepen the analysis on the relationship that has been established between gender and digital games.

The U-Constructs and Mobile Usage Behavior: Development and Validation of the U-Feat Scale

Information systems researchers have suggested that the world would move to Uber Commerce (U-Commerce) with a high degree of personalization. However, research in measuring U-Commerce constructs (ubiquity, universality, uniqueness, and unison) is sparse, and out of the 4 U-constructs, only perceived ubiquity has a measurement scale. In the present study, we construct reliable and valid measures for the three other (excluding Perceived Ubiquity) U-constructs. To this end, the study uses a stepwise approach starting from theoretical and qualitative exploration (using focus groups) and follows up with survey research (sampling 250 students and 326, 311, and 511 nonstudents in four consecutive surveys, respectively). Using exploratory and confirmatory factor analysis, the study develops reliable and valid multidimensional scales for the three U-constructs. Subsequently, the three U-construct scales are integrated with perceived ubiquity to form a comprehensive higher order scale named U-Feat, and it is validated in a nomological network of antecedents and consequences. U-Feat was found to have a significant effect on U-Commerce adoption.

The new Gold Standard in Online Delivered Behavioral Health Programs

Recent reforms in the US healthcare space are seeing an exponential increase in demand for care and also a regulation of esteem between physical and behavioral healthcare. Healthcare providers are under increasing pressure to provide cost-effective and high quality services to a large number of individuals. Online delivered interventions have the potential to provide a solution to healthcare providers as they can provide accessible and flexible healthcare. Online delivered behavioral health programs have developed an empirical base. The majority of this evidence-base has originated in Europe and Australia. The US healthcare market is now in a position to realize the benefits of online delivered behavioral health programs that offer excellent solutions to many of the difficulties in accessing behavioral healthcare in the US. While some guidelines and other operational characteristics have been developed, no standard setting out what is required of any connected health intervention is established. The US can look to the empirical base from developments and research worldwide, and also to thought leaders who are integrating the available evidence-base to shape standards of excellence for the future of online delivered behavioral health interventions. To that end the poster outlines some of the attributes, drawn from the evidence-base, that could be considered to be some of the necessary criteria needed to characterize any Gold Standard intervention. This set of attributes would therefore define excellence in connected healthcare delivery and help inform best practice. It is therefore proposed that a gold standard online-delivered program for behavioral health should include at least some of the following points: 1. Include the use of evidence-based and empirically supported content 2. Focus on accountable care and deliver on effective clinical outcomes 3. Be developed on robust, engaging, secure and responsive technologies 4. Be informed and shaped by behavioral health subject matter experts’ clinical expertise 5. Be patient-centric: involve users in the development and evaluation process and a high degree of personalization 6. Have research and evaluation that supports its effectiveness

ONTOTV: AN ONTOLOGY-BASED SYSTEM FOR THE MANAGEMENT OF INFORMATION ABOUT TELEVISION CONTENTS

Nowadays, there are a huge number of digital television platforms and channels, so it is not easy for the viewer to decide what they want to watch. Some television providers offer information about the programs they broadcast, but this information is usually scarce and there is no possibility to perform advanced operations like recommendation ones. For this reason, viewers could benefit from a system that integrates all the available information about contents, and applies semantics methodologies in order to provide a better television watching experience. The main objective of this research is the design of a television content management system, called OntoTV, which retrieves television content information from various existing sources and represents all these data in the best way possible by using knowledge engineering and ontologies. These semantic computing techniques make it possible to offer the viewers more useful operations on the stored data than traditional systems do, and with a high degree of personalization. Additionally, OntoTV accomplishes all of this regardless of the TV platform installed and the client device used. The viewers' satisfaction when using this system has been also studied to prove its functionality.

Effects of Personalized Sponsorship of an Additional Covering Letter on Return Rate and Nature of Evaluative Response

Response rates to a questionnaire accompanied by a personal covering letter with or without an additional highly personal covering letter were investigated. 2 male and 94 female former trainees of an Occupational Therapy Training Program were sent questionnaires designed to evaluate their training experience. A significantly greater number of returns were received from the former trainees who received both a personalized covering letter and a “highly personalized” covering letter from a former supervisor. An investigation of the prediction that a high degree of personalization also would favorably bias the nature of the evaluative response was not substantiated. The results suggested that personalization offers advantage to scientific investigation, especially that in program evaluation without seriously affecting financial or methodological cost.