Individual Preferences Research Articles

How to promote knowledge transfer within R&D team? An evolutionary game based on prospect theory

Knowledge transfer is the basis for R&D teams and enterprises to improve innovation performance, win market competition and seek sustainable development. In order to explore the path to promote knowledge transfer within the R&D team, this study considers the bounded rationality and risk preference of individuals, incorporates prospect theory into evolutionary game, constructs a perceived benefits matrix distinct from the traditional benefits matrix, and simulates the evolutionary game process. The results show that, R&D personnel’s knowledge transfer decisions depend on the net income difference among strategies; only if perceived cost is less than the sum of perceived synergy benefit, perceived organization reward value, and perceived organization punishment value, can knowledge be fully shared and transferred within the R&D team. Moreover, R&D personnel’s knowledge transfer decisions are interfered by the irrational psychological factors, including overconfidence, reflection, loss avoidance, and obsession with small probability events. The findings help R&D teams achieve breakthroughs in improving the efficiency of knowledge transfer, thereby enhancing the capacity of enterprises for collaborative innovation.

Directive Explanations for Actionable Explainability in Machine Learning Applications

In this article, we show that explanations of decisions made by machine learning systems can be improved by not only explainingwhya decision was made but also explaininghowan individual could obtain their desired outcome. We formally define the concept ofdirective explanations(those that offer specific actions an individual could take to achieve their desired outcome), introduce two forms of directive explanations (directive-specific and directive-generic), and describe how these can be generated computationally. We investigate people’s preference for and perception toward directive explanations through two online studies, one quantitative and the other qualitative, each covering two domains (the credit scoring domain and the employee satisfaction domain). We find a significant preference for both forms of directive explanations compared to non-directive counterfactual explanations. However, we also find that preferences are affected by many aspects, including individual preferences and social factors. We conclude that deciding what type of explanation to provide requires information about the recipients and other contextual information. This reinforces the need for a human-centered and context-specific approach to explainable AI.

Analisis Komparasi Metode Sistem Pendukung Keputusan pada Gaya Belajar “VARK”

Learning style is an important factor in the success of the learning process from learning resources to individuals or groups. Understanding learning styles can be a strategy in the learning process. One of the learning styles is "VARK" which is the preference of individuals or learning groups consisting of visual, aural, read/write, and kinesthetic. Various methods are developed to find out the learning style of an individual or group of learners. In this research, a decision support system (SK) will be developed that provides learning style recommendations for individuals or study groups whether the tendency is visual, aural, read/write, or kinesthetic. The method used is a combination of simple additive weighting (SAW) and weighted product (WP). The SPK development stages consist of data collection through distributing surveys to 55 student respondents at the 1926 Education Foundation where the dominant characteristic of the respondent's learning style is visual, namely 56%, analyzing SAW and WP methods, developing SPK with a web-based system, testing the system using the black box testing method.

Clothing deveopment through the integration of autistic children: inclusion through social action

In this study on inclusive fashion for autistic children, a visit to a children's clothing store and a custom shirt customization activity were conducted with two autistic children from Criciúma/SC, aiming to promote their self-esteem and autonomy. Social inclusion and acceptance of diversity are increasingly relevant, driving the search for strategies that ensure the full participation of everyone in society. The study aimed to understand how to assist autistic children in the selection and use of clothing, recognizing that their sensory characteristics and individual preferences are important considerations. The research was carried out in partnership with a local children's store, where autistic children were engaged in clothing-related activities. During the store visit, there was a noticeable increase in the children's interaction with different styles and textures of clothing, highlighting the importance of options that cater to their sensory needs. The results demonstrated that these experiences facilitated greater interaction and integration of children with the fashion world, enhancing their autonomy, self-esteem, and facilitating the process of choosing and wearing different clothes. Furthermore, customization stimulated the children's creativity and increased their involvement in producing personalized prints on their own clothing items. The need to develop strategies and actions to promote the inclusion and appreciation of autistic children in the fashion industry is emphasized. This extends beyond adapted clothing to fostering welcoming environments in stores and encouraging active participation in the process of creating their own clothing and prints.

Physiological Indicators of Fluency and Engagement during Sequential and Simultaneous Modes of Human-Robot Collaboration

OCCUPATIONAL APPLICATIONS An understanding of fluency in human-robot teaming from a physiological standpoint is still incomplete. In our experimental study involving 24 participants, we designed a scenario for shared-space human-robot collaboration (HRC) for a material sorting task. When compared to a sequential mode of interaction, the simultaneous mode resulted in significantly higher perceptions of fluency and engagement, primarily by reducing human idle time. These observations were complemented by significant changes in physiological responses, such as ECG entropy and low frequency power. These responses could predict fluency and engagement with accuracies of 90 and 97%, respectively. Notably, the perception of fluency and preferred mode of interaction were influenced by individual preferences. Hence, it is crucial to consider both physiological responses and user preferences when designing HRC systems, to ensure a positive experience with the robot teammate and to foster engagement in long-term teamwork. Furthermore, these signals can be obtained using a single robust, low-cost, and comfortable sensor.

Individual preferences, jobs, or amenities? Understanding the destination choices of highly and less-skilled migrants in urban China

Existing research has explored the spatial patterns and determinants of labor migration but has not considered the heterogeneity of migrants. This paper compares the migratory behavior of highly and less-skilled migrants to provide a more nuanced understanding of internal migration in urban China. We employ a nested multinomial logit approach to assess the relative contribution of individual characteristics and city attributes in explaining migrants' destination choices. The findings reveal both similarities and differences in highly and less-skilled migration. Migrants share primary priorities: spatial proximity to hometowns, moving to cities situated higher in the administrative hierarchy, occupations, and wages. But more importantly, migrants of varying skill levels have different strategies as they navigate increasing economic opportunities and public services while simultaneously encountering a discriminatory hukou system. Highly skilled migrants are more mobile and prioritize their personal preferences; less-skilled migrants, although more restricted by gender, age, and hukou types and inclined for stability, tend to maximize their utility through temporary movement to large cities. Hence, policymakers of different cities should recognize people's heterogeneous migration behavior and design targeted policies.

The relaxation effect of autonomous sensory meridian response depends on personal preference.

Autonomous sensory meridian response (ASMR) is a sensory response such as tingling and pleasantness from audiovisual stimuli. ASMR videos come in a wide variety of types, and personal preferences are biased. There are many reports of the effects os ASMR on sleep onset, anxiety relief, and other relaxation effects. However, prior task-oriented studies have used ASMR videos provided by the experimenter. We hypothesized that ASMR movies of a personal preference would show significantly increased activity in the nucleus accumbens, frontal cortex, and insular cortex, which are brain areas associated with relaxation. Therefore, the purpose of this study was to elucidate the neuroscientific basis for the relaxation effects of ASMR videos that match someone's personal preferences. This study included 30 healthy individuals aged ≥18 years. ASMR enthusiasts were included as the target population due to the need to have a clear preference for ASMR videos. A control video (1 type) and ASMR videos (20 types) were used as the stimulus tasks. Among the ASMR videos, those with high and low evaluation scores were considered liked and dislikedASMR videos, respectively. Functional magnetic resonance imaging was performed while the participants viewed a block design with a resting task in between. The data were analyzed using Statistical Parametric Mapping 12 to identify the areas activated by control, disliked, and liked ASMR videos. Emotion-related areas (the amygdala, frontal cortex, and insular cortex) not activated by control and unliked ASMR videos were activated only by liked ASMR videos. The amygdala, frontal cortex, and insular cortex may be involved in the limbic dopamine circuits of the amygdala and middle frontal gyrus and the autonomic balance of the left and right insular cortices. This suggests the potential of positive mood and its use as a treatment for patients with anxiety and depression. These results suggest that the use of ASMR videos to match individual preferences may induce relaxation and have beneficial effects on depression and other disorders, and also support the introduction of ASMR videos in mental health care.

The Role of Artificial Intelligence (AI) and Data Analytics in Enhancing Guest Personalization in Hospitality

Purpose: The main objective of this study was to explore the role of Artificial Intelligence (AI) and data analytics in enhancing guest personalization.
 Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The findings revealed that there exists a contextual and methodological gap relating to the role of Artificial Intelligence (AI) and data analytics in enhancing guest personalization. Preliminary empirical review revealed the significant potential of AI and data analytics in transforming the hospitality industry by enhancing guest personalization. By offering personalized experiences that align with individual preferences, hotels can not only improve guest satisfaction but also drive revenue growth and customer loyalty. However, it is imperative for the industry to navigate the ethical considerations associated with data privacy to ensure that the benefits of personalization are realized without compromising guest trust and privacy. The findings of this study provide valuable insights for hoteliers, service providers, and policymakers looking to harness the power of AI and data analytics to create exceptional guest experiences in the evolving landscape of hospitality.
 Unique Contribution to Theory, Practice and Policy: The Technology Acceptance Model (TAM), Service Quality theory and Customer Relationship Management theory (CRM) may be used to anchor future studies on Artificial Intelligence and data analytics in modern hospitality. This study recommended for investing in robust AI and data analytics infrastructure, gathering comprehensive guest data, implementing AI driven personalization algorithms, empowering staff with AI tools and continuously monitoring and adapting.

Validation of the Arabic Version of the Patient Activation Measure (PAM-13) for Application within the Primary Healthcare Context in Saudi Arabia

Background: Empowering patients with behavioral issues or chronic conditions to actively participate in their healthcare can help improve health outcomes. However, in the Saudi Arabian context, evaluation tools for achieving this goal are lacking, considering cultural and healthcare system factors. Therefore, this study aimed to determine the psychometric properties of the Arabic version of the Patient Activation Measure. Methods: This cross-sectional validation study was conducted on a sample of 225 patients receiving treatment from primary healthcare centers located in Riyadh, Saudi Arabia. Item analyses and reliability and construct validity testing of the tool were conducted. Results: The item–total correlation coefficients ranged from 0.31 (item 2) to 0.57 (item 11). The item–total correlation coefficients for all 13 items were above 0.30. The reliability was 0.80. A two-factor model (“knowledge and beliefs” and “confidence and skills”) reflecting the instrument was constructed. The raw model did not sufficiently fit the data (χ2 = 170.98, degree of freedom (df) = 64, p < 0.001; Tucker–Lewis index (TLI) = 0.79; comparative fit index (CFI) = 0.83; root mean square error of approximation (RMSEA) = 0.86 [90% confidence interval {CI} = 0.07–0.10]). After all significant correlations between the items’ error terms were modeled, an adequate fit was achieved (χ2 = 76.76, df = 51, p < 0.01; TLI = 0.94; CFI = 0.96; RMSEA = 0.04 [90% CI = 0.02–0.07]). Conclusions: the Arabic version of the Patient Activation Measure can be utilized by healthcare providers to assess the activation levels and unique needs and preferences of Arabic-speaking individuals and tailor interventions accordingly to provide necessary support.

An Improved Similarity-based Fuzzy Group Decision Making Model through Preference Transformation and K-Means Clustering Algorithm

Group decision making plays a crucial role in organizational and community contexts, facilitating the exchange of expert opinions to arrive at effective decisions. The concept of preference, reflecting an individual's subjective evaluation of criteria or alternatives, forms a foundational element in this process. This study focuses on transforming non-fuzzy preferences, such as preference ordering and utility functions, into fuzzy preference relations (FPR) to address the uncertainty and uniformity inherent in expert preferences. To further enhance decision-making, we assess and visualize the similarity among the experts' uniform preferences. Integrating the K-means clustering algorithm into the fuzzy group decision making model allows for the predetermination of an appropriate number of groups based on the available alternatives. By aggregating individual preferences, we present a final ranking of alternatives. The enhanced methodology, as demonstrated through comparative analysis, showcases its ability to yield positive benefits when applied to decision-making applications.

Blood Lactate and Heart Rate Responses Between Active and Passive Recovery Modes Over a 15-Minute Recovery Period in Female Dancers After Kathak Dance.

Introduction: Dance is physically demanding and results in blood lactate (BL) accumulation and elevated Heart Rate (HR). Researchers recommend using either Active Recovery (AR; eg, low-to-moderate intensity-exercise) or Passive Recovery (PR; eg, complete rest) modes after activity. We compared BL and HR responses between AR or PR over a 15-minute recovery period following a Kathak dance. Methods: Twelve female dancers (31.0 ± 6.0 years; 161.5 ± 4.9 cm; 55.5 ± 5.8 kg) performed 2 dance testing sessions (Day 1 = AR, Day 2 = PR) 48 hours apart. Each session started with a 10-minute warm up followed by dancers performing four 2-minute stages of Kathak dance, with three 1-minute periods between stages where we recorded HR and their Rate of Perceived Exertion (RPE:scale = 6-20) to match the intensity of both sessions. Post-dance, we recorded dancers' BL and HR at 1, 3, 5, 10, and 15 minutes while they recovered via AR or PR. Separate 2(mode) × (time) Repeated-Measures-ANOVA followed by simple-main-effects testing and adjusted Bonferroni-pairwise-comparisons examined differences in BL and HR responses across modes and time(α = .05). Results: Dancers' HR and RPE were similar across sessions. No mode × time interaction existed in BL (F4,8 = 3.6, P = .06). BL levels were similar across modes (F1,2 = 0.5, P = .5). BL levels reduced over time (F4,8 = 6.0, P = .02), but Bonferroni-comparisons did not reveal any pairwise differences. In HR a significant mode*time interaction (F4,36 = 11.0, P = .01, η2 = .55) was observed. Both Active and Passive recovery modes achieved absolute HR levels by 15 minutes, with PR mode stabilizing within 5 minutes. Conclusions: Over a 15-minute recovery period after Kathak dance, dancers' BL and HR responses were similar across time in both AR and PR, with HR being higher in AR. Dancers' HR remained similar from 1 to 3 minute post dance recovery and then dropped over time. Thus, dancers can rest up to 3 minutes and still maintain the same elevated HR. Overall, dancers can choose either AR or PR as their recovery mode based on their individual preferences.

Exploring the Association Between Trunk Asymmetry and Dominance Preference

Background: Trunk asymmetry, an indicator of potential scoliosis, manifests as an uneven distribution in body alignment such as shoulder, head, and hip positions. An individual's inherent preference to use one side of the body over the other, known as laterality, may contribute to such imbalances. This study aimed to explore the correlation between trunk asymmetry and side preference in adults, particularly in relation to hand, foot, ear, and eye dominance. Methodology: In this cross-sectional study, 164 young adults aged 18-25 were screened using the Adam’s forward bend test. Data collection encompassed three phases: demographic and anthropometric data collection (Phase 1), a visual inspection for head tilt, shoulder and pelvic asymmetry, and spinal curvature deviation (Phase 2), and an assessment of side dominance using a 16-item lateral preference inventory questionnaire (Phase 3). Results: Hand dominance correlated significantly with head tilt (p < 0.01), shoulder asymmetry (p < 0.05), and ear asymmetry (83.5% concordance), while foot dominance was associated with pelvic tilt (57.3% concordance). Eye dominance showed a 65.9% concordance with ear asymmetry, and ear dominance was linked to head tilt and shoulder asymmetry (81.7% and 94.5% concordance, respectively). Spinal curve deviation displayed a chi-square value of 3.158 (p < 0.05) with hand dominance and 4.321 (p < 0.05) with foot dominance. Conclusion: The study establishes a significant association between trunk asymmetry and dominance preference. These findings advocate for the integration of laterality assessments in the clinical evaluation of trunk asymmetry to potentially enhance diagnostic accuracy and inform therapeutic approaches.

Vertical greening systems serve as effective means to promote pollinators: Experimental comparison of vertical and horizontal plantings

To counteract the ongoing decline of pollinators, we need innovative and effective promotion strategies. Urban areas often function as pollinator refugia, but lack of open spaces can limit promotion measures. This scarcity in open surfaces requires rethinking the conventional flower bed. Can green walls, planted with pollinator-friendly plants, provide an alternative and attractive food source for wild and managed pollinators?We compared pollinator-friendly vertical greening systems covering approximately 6 m2 with identically planted, adjacent horizontal beds consisting of wild perennials and cultivated plant varieties at two different test sites in Baden-Württemberg, Germany. With a total of 92 planting observations and more than 2,800 single plant genera observations, we documented 12,963 pollinators and their individual plant preferences over a two-year period.While our results show no differences in the total attractiveness across all pollinators between vertical systems and horizontal plantings, honey bees had a highly significant preference for the horizontal plantings, while wild bees preferred the vertical systems. Pollinator visits increased with the height of the vertical systems, indicating that pollinators will find such vertical sources and that there are advantages to higher plantings above foot traffic. These results suggest that vertical systems are highly attractive spaces for flower visitors, especially for bumble bees and other wild bees, when planted with appropriate blooming plants and thus an innovative means to promote pollinators where horizontal open spaces are limited.

Tourist Guide AI

Abstract—The research paper presents an innovative AI-driven platform that revolutionizes the landscape of personalized travel recommendations within specific cities. Leveraging the power of Artificial Intelligence (AI), the "Tourist Guide AI" system offers curated suggestions for attractions, activities, and dining options based on individual preferences. The platform integrates machine learning algorithms, geospatial data, and natural language processing to provide comprehensive insights into city attractions, ensuring a personalized and enriching travel experience. The deployment phase involves launching the system on cloud servers, ensuring widespread accessibility and scalability to accommodate varying user demands. The methodology employed encompasses rigorous data collection, preprocessing, and the implementation of a recommendation algorithm that combines collaborative and contentbased filtering techniques. The user interface is designed with intuitiveness and user- friendliness at its core, ensuring an intuitive experience for travelers of all backgrounds. The platform's advantages include personalized recommendations, efficient trip planning, real-time updates, and potential integration with mobile devices for on-the-go guidance. The research paper also acknowledges potential disadvantages and limitations, such as data accuracy, privacy concerns, and limited coverage for remote or lessvisited destinations, emphasizing the commitment to continuous improvement and expansion of coverage. The "Tourist Guide AI" project represents a significant step towards simplifying and enriching the tourist planning process, ensuring that each trip is a unique and tailored adventure for travelers of all backgrounds and preferences. Keywords—Tourist Guide AI, places recommendation, OpenAI APIs, Tourism form AI,Content Based Filtering, Vectorization .

Post-occupancy evaluation of thermal comfort at studio classroom in hot and humid climate

Thermal comfort is crucial in providing a productive learning environment, especially in the design studio classroom with a longer lecture duration (09.00-15.00). This study aims to investigate the thermal performance ability to provide thermal comfort for its users in a design studio classroom at Universitas Indonesia, Depok. Ninety-one students (20% Male, 80% Woman) aged 19-22 years old were surveyed about their thermal perspective by using TSV, TP, HSV, HP, metabolic rate (MET), and clothing insulation (clo). Field measurement recorded humidity and temperature conditions over two lecture periods. The indoor operative temperature for periods A and B was 27.28°C and 26.78°C, respectively, with TSV values in both periods within the comfort temperature range (mean: (A) -0.30, (B) -0.58). However, TP values suggest that the users prefer a slightly cooler condition with values of -1.53 and -1.12, respectively, for Periods A and B. The results show that studio classrooms can perform thermally well even though some users prefer slightly cooler temperatures. This study scored the necessity of understanding both subjective and objective aspects of thermal comfort to create an optimal learning environment. Findings suggest that further study should consider variations in individual preferences and the influence of external environmental factors.

Optimal Subscription Policies for Participation-Dependent Social-Learning Markets

In this work we study the economic interactions that arise between a service provider and a collection of users in a participation-dependent social-learning market. Specifically, we consider a two-stage model of a market where the objective of the service provider is to design attractive subscription policies (i.e., subscription price-period combo) so as to maximize its overall revenue. The users on the other hand make subscription decisions based on their individual preferences (private information) as well as the feedback given by the earlier subscribers (public information). For the proposed two-stage model, taking into account the statistical differences between the users who subscribed to stage-1 (i.e., promotional period) and those who did not, we derive the optimal price for stage-2 (i.e., operational period) for each possible history of the stage-1 process. Then, employing the technique of dynamic programming we derive the Bellman’s optimality equation, solving which yields the optimal subscription policy for stage-1. Using the structure of the optimal policy as a guideline, we propose a range of heuristic policies by relaxing some key aspect(s) of the optimal policy. Finally, we conduct an extensive numerical study to benchmark the efficacy of the optimal policy (in terms of the average revenue accrued by the provider) against the proposed heuristic policies.

The Role of Object Physical Properties in Human Handover Actions: Applications in Robotics

Observing how humans interact with each other and how they manipulate objects, offer insight on interaction mechanisms and how these are influenced by the physical properties of the used objects. These insights can support a more informed design of robot controllers meant to manipulate objects in collaboration with humans. In this work we study human-to-human handovers of cups filled with various amount of liquid and textures, and investigate to which extent the manipulation strategy depends on: (i) the individual preference, (ii) whether the cup is filled with water or not, and (iii) the cup physical properties. An analysis of the human giver’s hand acceleration, velocity, and position during the handover of different cups under two liquid level conditions, allows to distinguish between careful and not-careful (normal) manipulation. We quantify to which extent the liquid level inside the cups influences the carefulness level of human manipulation. Lastly, our study reveals that the cups’ physical properties, such as fragility, breakability, and deformability, play a role in shaping the carefulness of the manipulation. We apply these findings to human-robot scenarios by developing a robot controller capable of detecting, in real-time, if the human is being more careful than normal, and adapting the robot’s approach of interaction accordingly. Additionally, we show that the detection of a careful manipulation, depending on the experimental context, may provide the robot with information concerning the human partner’s intention or need for (manipulation) assistance.

Treatments for obstructive sleep apnea: CPAP and beyond.

Treatment options for obstructive sleep apnea include positive airway pressure and alternatives such as behavioral interventions, oral appliances, nasal expiratory positive airway pressure, negative pressure interventions, and surgical procedures. Certain drugs are also promising. An important aspect of the treatment includes troubleshooting the reasons for poor adherence to positive airway pressure treatment, discussing alternatives based either on individual preference or on phenotypic characterization of the sleep apnea, and managing expectations.

Eliciting preferences of persons with dementia and informal caregivers to support ageing in place in the Netherlands: a protocol for a discrete choice experiment

IntroductionAgeing in place (AIP) for persons with dementia is encouraged by European governments and societies. Healthcare packages may need reassessment to account for the preferences of care funders, patients and...

AN ANALYSIS OF THE ROLE OF OVER-THE-TOP (OTT) PLATFORMS IN THE CHANGING FACE OF INDIA'S FILM AND TELEVISION INDUSTRY

The present study aims to examine the OTT consumption patterns of individuals, utilizing a sample size of 110 participants. The objective of this study is to acquire a comprehensive understanding of individual OTT content preferences and watching habits. This study utilized a quantitative research methodology and employed surveys as the major means of data collection. The survey questionnaire encompasses variables pertaining to social media platforms, over-the-top (OTT) platforms, and the devices employed all crucial factors for comprehending individuals patterns of OTT consumption. This study indicates that the majority of viewers prefer Disney+ Hotstar, then Netflix, and finally other over-the-top (OTT) platforms. According to the findings of this study, the cost (high membership fees) and the need for advanced network and technological capabilities pose the greatest barrier to the use of OTT platform services.