Unique Behavioral Patterns Research Articles

The Cost of Free: The Behavioral Economic Effects of 'Wait-for-Free' Pricing Schemes on the Monetization of Hedonic Digital Content

Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, pleasure-seeking digital content that has become increasingly pervasive in online platforms. WFF pricing is a strategy in which consumers are given the option to either wait for a certain amount of time to acquire indulgent digital content at no charge or pay to consume it immediately. We evaluate the extent to which habit formation and present-biased preferences driven by the consumption of addictive stock affect individual consumers’ willingness to wait and pay for content, which, in turn, determines the efficacy of WFF pricing. We also devote attention to consumer switching from awaiting free content to instantaneously consuming through purchase under the scheme of interest. The findings indicate that WFF pricing increases sales from serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively secures sustained profits over long periods. We found that approximately 80% of consumers who initiate purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, we found that as a user consumes an accumulation of freely available episodes given extended waiting, the risk of conversion from delayed gratification to purchase increases. In particular, WFF pricing effectively augments the willingness-to-pay of low-valuation consumers as habit formation builds up through time with free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 28%. However, as the number of free episodes consumed upon waiting goes beyond a threshold, the risk of conversion decreases. The analytical and empirical findings offer valuable insights into how consumers’ unique behavioral patterns (i.e., habit-formation and present bias) affect their willingness to pay for highly addictive digital goods. We conclude with a discussion of the pricing mechanism’s application in other contexts wherein consumers are willing to pay for immediate satisfaction rather than wait for complementary consumption.

We love to hate them! Social media-based anti-brand communities in professional football

Purpose Social media has promoted anti-brand communities, which build around the shared aversion to a specific brand. The purpose of this paper is to investigate social media-based anti-brand communities and their effects on the sports team brand in question. Design/methodology/approach The authors conducted a netnographic study of Facebook-based anti-brand communities that oppose a professional football team. Findings The netnographic study reveals characteristics and drivers of Facebook-based anti-brand communities that oppose a professional football team. The research further identifies co-destructive behaviours of anti-brand community members that harm the sports team brand and even its sponsors. However, the findings also reveal that anti-brand communities may play a positive role in sport, as they strengthen the relationship between fans of the opposed brand and this brand and foster rivalry among football fans. Practical implications This research establishes the relevance of social media-based anti-brand communities for sports brands. Recommendations are made for team sport brands with regards to how to deal with the phenomenon of anti-brand communities. Originality/value While the previous research on anti-brand activism focused on either offline movements or movements using traditional websites, this research is the first to investigate the pivotal role of social networking sites for anti-brand activism. The paper further uncovers unique motivational, attitudinal, and behavioral patterns of fans that meet in communities opposing not only the rival team, but also the brand associated with the team. Findings show ways to better understand and deal with such anti-brand communities in sports.

Rekening Bersama (RekBer) The Indonesian Escrow Service of Money

That was a common thing when Escrow Service of Money (ESM) providers handled by the institution that has a legal aspect (structural assurance) to operates their business activities. However, how if the bank-like service agency operates by the individual, performed online and does not have some guaranteeing assets? How they do warrant their customers that they will not violate the consumer trusts? In addition, did the customers trust them? In this paper appointed a case study of the Rekening Bersama (RekBer) phenomenon as Indonesian ESM. Where, most of them ran the bank-like business without forming a legal entity as a reliable guarantee. In spite of that, we found a unique behavioral pattern that either incorporated RekBer or individual RekBer has the same opportunity to being trusted by their trustors.

Biological activity of the bryostatin analog Merle 23 on mouse epidermal cells and mouse skin.

Bryostatin 1, a complex macrocyclic lactone, is the subject of multiple clinical trials for cancer chemotherapy. Although bryostatin 1 biochemically functions like the classic mouse skin tumor promoter phorbol 12-myristate 13-acetate (PMA) to bind to and activate protein kinase C, paradoxically, it fails to induce many of the typical phorbol ester responses, including tumor promotion. Intense synthetic efforts are currently underway to develop simplified bryostatin analogs that preserve the critical functional features of bryostatin 1, including its lack of tumor promoting activity. The degree to which bryostatin analogs maintain the unique pattern of biological behavior of bryostatin 1 depends on the specific cellular system and the specific response. Merle 23 is a significantly simplified bryostatin analog that retains bryostatin like activity only to a limited extent. Here, we show that in mouse epidermal cells the activity of Merle 23 was either similar to bryostatin 1 or intermediate between bryostatin 1 and PMA, depending on the specific parameter examined. We then examined the hyperplastic and tumor promoting activity of Merle 23 on mouse skin. Merle 23 showed substantially reduced hyperplasia and was not tumor promoting at a dose comparable to that for PMA. These results suggest that there may be substantial flexibility in the design of bryostatin analogs that retain its lack of tumor promoting activity. © 2016 Wiley Periodicals, Inc.

Where You Are Is Who You Are: User Identification by Matching Statistics

Most users of online services have unique behavioral or usage patterns. These behavioral patterns can be exploited to identify and track users by using only the observed patterns in the behavior. We study the task of identifying users from statistics of their behavioral patterns. Specifically, we focus on the setting in which we are given histograms of users' data collected during two different experiments. We assume that, in the first dataset, the users' identities are anonymized or hidden and that, in the second dataset, their identities are known. We study the task of identifying the users by matching the histograms of their data in the first dataset with the histograms from the second dataset. In recent works, the optimal algorithm for this user identification task is introduced. In this paper, we evaluate the effectiveness of this method on three different types of datasets and in multiple scenarios. Using datasets such as call data records, web browsing histories, and GPS trajectories, we show that a large fraction of users can be easily identified given only histograms of their data; hence these histograms can act as users' fingerprints. We also verify that simultaneous identification of users achieves better performance compared to one-by-one user identification. We show that using the optimal method for identification gives higher identification accuracy than heuristics-based approaches in practical scenarios. The accuracy obtained under this optimal method can thus be used to quantify the maximum level of user identification that is possible in such settings. We show that the key factors affecting the accuracy of the optimal identification algorithm are the duration of the data collection, the number of users in the anonymized dataset, and the resolution of the dataset. We analyze the effectiveness of k-anonymization in resisting user identification attacks on these datasets.

Authentication based on keystroke dynamics using stochastic diffusion algorithm

ABSTRACTAuthentication plays an important role in dealing with security. Securing sensitive data and computer systems by allowing easy access for authenticated users and withstanding the attacks of imposters is one of the major challenges in the field of computer security. Nowadays, passwords have become the trend to control access to computer systems. Biometrics are used to measure and analyze an individual's unique behavioral or physiological patterns for authentication purposes. Keystroke dynamics have emerged as an important method in analyzing the typing rhythm in biometric techniques, as they provide an ease of use and increased trustworthiness associated with biometrics for creating username and password schemes. In this experiment, we measure the Hausdorff timing values, mean, standard deviation, and median of keystroke features, such as latency, duration, digraph, and their combinations, and compare their performance. The stochastic diffusion search is used for feature subset selection.

Neural activation patterns underlying basolateral amygdala influence on intra-accumbens opioid-driven consummatory versus appetitive high-fat feeding behaviors in the rat.

The present study explored the role of the amygdala in mediating a unique pattern of feeding behavior driven by intra-accumbens (intra-Acb) opioid activation in the rat. Temporary inactivation of the basolateral amygdala (BLA), via GABAA agonist muscimol administration prevents increased consumption following intra-Acb opioid administration of the selective μ-opioid agonist D-Ala2, NMe-Phe4, Glyol5-enkephalin (DAMGO), yet leaves food approach behaviors intact, particularly after consumption has ended. One interpretation is that inactivation of the BLA selectively blocks neural activity underlying DAMGO-driven consummatory (consumption) but not appetitive (approach) behaviors. The present experiments take advantage of this temporal dissociation of consumption and approach behaviors to investigate their associated neural activity. Following either intra-Acb saline or DAMGO administration, with or without BLA muscimol administration, rats were given 2-hr access to a limited amount of high-fat diet. Immediately following the feeding session, rats were sacrificed and brains assayed for neural activity patterns across critical brain regions known to regulate both appetitive and consummatory feeding behaviors. The results show that intra-Acb DAMGO administration increased c-Fos activation in orexin neurons within the perifornical area of the hypothalamus and that this increase in activation is blocked by BLA muscimol inactivation. Intra-Acb DAMGO administration significantly increased c-Fos activation within dopaminergic neurons of the ventral tegmental area, compared to saline controls, and BLA inactivation had no effect on this increase. Overall, these data provide underlying circuitry that may mediate the selective influence of the BLA on driving consummatory, but not appetitive, feeding behaviors in a model of hedonically driven feeding behavior.

Evaluation of the relationship between lifestyle and body mass index in administrative employees of Bojnourd, Iran

Background and Purpose: Lifestyle is defined as the unique behavioral patterns and habits of an individual. If lifestyle is imbalanced, risk of illnesses and burdensome events increases. Lifestyle plays a key role in the modulation of body mass index (BMI) and prevention of obesity. This study aimed to investigate the relationship between lifestyle and BMI in the administrative employees of Bojnourd, Iran in 2014. Materials and Methods: This cross-sectional study was conducted on 380 government employees selected by stratified random sampling with proportional allocation in each stratum. Data were collected using prepared checklists and lifestyle questionnaires. Weight and height of subjects were measured using standardized methods. Data analysis was performed using descriptive statistics and Pearson’s correlation coefficient in SPSS V.18. Results: In this study, frequency of lifestyle was 4.58%, 52.48% and 42.94% in scoring scales of favorable, relatively favorable and unfavorable, respectively. Moreover, 6.6% of the subjects were underweight, 34.7% were normal, 36.1% were overweight, and 21.8% were obese. A significant correlation was observed between BMI and age (P=0.000), gender (P=0.03), physical exercise (P=0.04) and nutrition status (P=0.003) of the subjects. Conclusion: According to the results of this study, lack of physical activity and improper diet are the most important causes of obesity among administrative employees. Therefore, modification of lifestyle should be mandatory in order to improve BMI and overall health of these individuals.

A Qualitative Study of Smoker Identity Among College Student Smokers

Background: This research was motivated by findings that college students who smoke cigarettes often self-categorize as nonsmokers, that is, they reject the social identity of “smoker.” Objectives: The goal of the present study was to shed light on college students’ smoker identities beyond the smoker/nonsmoker dichotomy. Methods: Focus groups were conducted to investigate how college students categorize their own smoking patterns and to identify what behaviors and attitudes are associated with these different categories of smoker identities. Forty-one students from a western university participated in this study in November 2011. Results: The focus group results indicated that there were five distinct smoker identities on campus. Light and regular smokers were the daily smoker identities present, while stress, social, and drunk smokers were the occasional smoker identities. Moreover, each of these smoker identities was defined by a unique pattern of smoking behavior, attitudes, and motives. Conclusions/Importance: These findings support the notion that there are different types of smokers, both daily and occasional, in the college population. We suggest that researchers, healthcare providers, and prevention/intervention programs may all benefit from distinguishing between these different types of smokers.

User Identification Across Social Media

People use various social media sites for different purposes. The information on each site is often partial. When sources of complementary information are integrated, a better profile of a user can be built. This profile can help improve online services such as advertising across sites. To integrate these sources of information, it is necessary to identify individuals across social media sites. This paper aims to address the cross-media user identification problem. We provide evidence on the existence of a mapping among identities of individuals across social media sites, study the feasibility of finding this mapping, and illustrate and develop means for finding this mapping. Our studies show that effective approaches that exploit information redundancies due to users’ unique behavioral patterns can be utilized to find such a mapping. This study paves the way for analysis and mining across social networking sites, and facilitates the creation of novel online services across sites. In particular, recommending friends and advertising across networks, analyzing information diffusion across sites, and studying specific user behavior such as user migration across sites in social media are one of the many areas that can benefit from the results of this study.

Heterogeneity of alcohol, tobacco, and other substance use behaviors in U.S. college students: A latent class analysis

PurposeTo identify subgroups of college students with distinct profiles of traditional and alternative types of tobacco, alcohol, and other substance use and to examine how demographic characteristics and academic and social activities are associated with subgroup membership. MethodsWe used latent class analysis to characterize subgroups of individuals in their fourth-year of college based on their patterns of seven substance use behaviors: extreme heavy episodic drinking (HED), cigarette use, cigar/cigarillo/little cigar use, smokeless tobacco use, hookah use, marijuana use, and non-medical prescription drug use. Demographic characteristics and academic and social activities were then incorporated as predictors of these latent classes. ResultsWe identified five classes defined by unique behavior patterns: (1) Non/Low Users, (2) Non-Hookah Tobacco Users, (3) Extreme HED & Marijuana Users, (4) Hookah and Marijuana Users, and (5) Poly-Substance Users. Being male, older, and involved in sports were associated with greater odds of being in the Poly-Substance User class compared to the Low/No User class, and participating in an honors society and reporting more positive peer relationships were associated with being in the Hookah and Marijuana User class compared to the Low/No User class. ConclusionOur findings of unique characteristics in the subgroups identified suggest that college substance users are a heterogeneous population requiring different targeted interventions. Of particular concern are subgroups with high rates of alternative tobacco products, as perceived risks of use may be inaccurate and this is not currently a focus of college substance use prevention interventions.

A cloud based architecture capable of perceiving and predicting multiple vessel behaviour

Progressively huge amounts of data, tracking vessels during their voyages across the seas, are becoming available, mostly due to the automatic identification system (AIS) that vessels of specific categories are required to carry. These datasets provide detailed insights into the patterns vessels follow, while safely navigating across the globe, under various conditions. In this paper, we develop an Artificial Neural Network (ANN) capable of predicting a vessels future behaviour (position, speed and course), based on events that occur in a predictable pattern, across large map areas. The main concept of this study is to determine if an ANN is capable of inferring the unique behavioural patterns that each vessel follows and successively use this as a means for predicting multiple vessel behaviour into a future point in time. We design, train and implement a proof of concept ANN, as a cloud based web application, with the ability of overlaying predicted short and long term vessel behaviour on an interactive map. Our proposed approach could potentially assist in busy port scheduling, vessel route planning, anomaly detection and increasing overall Maritime Domain Awareness.

Environmental Studies and Researches Institute, University of Sadat City, Egypt

Reinforced concrete deep beams may exist in many structural applications such as offshore structures,transfer girders, pile caps, tall buildings and water tanks. The depth of deep beams is much greaterthan normal in relation to their span. Since the beam is short in this case, shear deformations are moreimportant and special design methods should be applied in this case rather than normal beam theory.Continuous deep beams are defined in the Egyptian Code of Practice (2012) [2]as those beams whoseheight to effective span ratio greater than 0.4. Deep beams are members with special features. In suchbeams, plane sections do not remain plane after bending, with significant warping of the crosssectionsbecause of high shear stresses. The resulting strain distribution is no longer linear andflexural stresses are not linearly distributed even in the elastic range. Recently, high strengthconcrete, defined by the American Concrete Institute ACI318-08[3], as concrete with cylindercompressive strength greater than 60Mpa, is being widely used in the construction industry.However, limited research efforts were directed towards the study of the behavior and shear strengthof reinforced high strength concrete continuous deep beams. Furthermore, sometimes web openingshave to be provided in deep beams for the purpose of access or for providing services. The presenceof such openings may affect the shear strength of deep beams. However, limited investigations weredirected towards the study of continuous deep beams with openings. Also, strengthening simplysupported deep beams using carbon fiber reinforced polymers (CFRP) was investigated by manyresearchers. However, limited research papers were directed towards CFRP strengthening ofcontinuous deep beams. Experimental tests have been carried out on rectangular reinforced concretecontinuous deep beams with a/d=1.17, under static loading up to failure. The study takes intoconsideration the following parameters: Percentage of web reinforcement (ρh), Positions ofopenings and number of openings. Also, strengthening of openings in continuous deep beams usingglass fiber reinforced polymer (GFRP) was studied in this research. Test results indicated that thepresence of web openings within exterior or interior shear spans had great effect on the beamcapacity and its behavior. Existence of web openings within exterior or interior shear spans caused ahigh reduction in the shear capacity of the beams by about 35%. Therefore and whenever should be kept clear of the natural load path joining the loading and reaction points (solid) free from openings.Also, the strengthening of openings contains the cracks and increase the crack and ultimate load.Finally we will compare the test results with the theoretical values for beam A1 which were evaluatedusing strut and tie analysis according to Egyptian code (2012). The strut–and tie method can be used forthe design of Disturbed regions (D- regions) of structures where the basic assumption of flexure theorynamely plane sections remaining discontinuities arising from concentrated forces or reactions and neargeometric discontinuities such as abrupt changes in cross section etc. The strut – and- tie method ofdesign is based on the assumption that the D-regions in concrete structures can be analyzed and designusing hypothetical pin-jointed trusses consisting of struts and ties interconnected at nodes. The usualdesign practice for continuous deep beams has been to employ empirical equations which are invariablybased on simple span deep beams testes. Given the unique behavior pattern of continuous deep beams,this practice is unreliable. Since continuous deep beams contain significant extents of D-regions and theyexhibit a marked truss or tied arch actions, the strut- and – tie method offers a rational basis for theanalysis and design of such beams. The mechanics and behavior of continuous deep beams are brieflydiscussed from which a strut–and–tie model for such a beam is developed.

Age-related changes in the intrinsic functional connectivity of the human ventral vs. dorsal striatum from childhood to middle age

The striatum codes motivated behavior. Delineating age-related differences within striatal circuitry can provide insights into neural mechanisms underlying ontogenic behavioral changes and vulnerabilities to mental disorders. To this end, a dual ventral/dorsal model of striatal function was examined using resting state intrinsic functional connectivity (iFC) imaging in 106 healthy individuals, ages 9–44. Broadly, the dorsal striatum (DS) is connected to prefrontal and parietal cortices and contributes to cognitive processes; the ventral striatum (VS) is connected to medial orbitofrontal and anterior cingulate cortices, and contributes to affective valuation and motivation. Findings revealed patterns of age-related changes that differed between VS and DS iFCs. We found an age-related increase in DS iFC with posterior cingulate cortex (pCC) that stabilized after the mid-twenties, but a decrease in VS iFC with anterior insula (aIns) and dorsal anterior cingulate cortex (dACC) that persisted into mid-adulthood. These distinct developmental trajectories of VS vs. DS iFC might underlie adolescents’ unique behavioral patterns and vulnerabilities to psychopathology, and also speaks to changes in motivational networks that extend well past 25 years old.

SETING PERILAKU DAN TERITORIALITAS RUANG SEBAGAI PERWUJUDAN ADAB DI MASJID GADING PESANTREN KOTA MALANG

This study concerns behavior setting and territoriality in Masjid Gading Pesantren as a part of the broader research on community based mosques and social interaction within them. The purpose is to identify some unique behavior patterns of the users of Masjid Gading Pesantren from the perspective of behavioral based research in architecture. The methods employed in this research are place-centered mapping, architectural documenting, and informal interview. The finding shows some specific behavioral pattern of the mosque’s users derived from the courtesy toward the mosque and the leader of the mosque as well as the pesantren. The behaviors form pattern as they become the tradition or local custom deriving into unique courtesy. Furthermore, this behavioral pattern also shapes the specific territories in the mosque, namely mihrab as a primary territory ‘owned’ by the kyai and legitimated by the santris. Such unique behavioral pattern belongs to local value which is largely accepted in Islam as long as it does not contradict with syariah.

Market closings and concentration of stock trading: an empirical analysis

We adopt a power law framework to measure the concentration of daily trading among the different stocks on the US market. Our analysis of the trends of daily concentration over the last five decades reveals that trading concentration is lower on Mondays and the day after a long weekend. These findings are supportive of the hypothesis that firms manage information release. We also find lower concentration at the end of December and in January. The results are consistent with our expectations for a stock market that comprises multiple groups of traders with unique trading behaviour and timing patterns.

Individual Differences in Children’s Early Strategy Behavior in Arithmetic Tasks

As demonstrated by the Overlapping Waves Model (Siegler, 1996), children’s strategy use in arithmetic tasks is variable, adaptive, and changes gradually with age and experience. In this study, first grade elementary school children (n = 73), who scored high, middle, or low in a standardized scholastic mathematic achievement test, were confronted with different arithmetic tasks (simple addition, e.g., 3 + 2, simple subtraction, e.g., 7 – 2, and more advanced addition, e.g., 7 + 9) to evoke different calculation strategies. Video analysis and children’s self-report were used to identify individual strategy behavior. In accordance with the Overlapping Waves Model, children in all achievement groups showed variable and multiple strategy usage and adapted their behavior to the tasks of the different categories. We demonstrated that not only low achievers differed from normal achievers but also that high achievers exhibited a unique pattern of strategy behavior in early mathematics.

Structural Analysis of User Association Patterns in University Campus Wireless LANs

Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. Such wide adoptions of new technologies will impact user behavior and in turn will affect network performance. It is imperative to characterize the fundamental structure of wireless user behavior in order to model, manage, leverage and design efficient mobile networks. One major challenge in characterizing user behavior stems from the significant size and complexity of user behavioral data. Without summarization and dimension reduction, the sheer amount of data does not provide much useful information. The key contribution of the paper is a novel similarity metric based on a matrix representation of mobility preferences and its decomposition. This method provides an efficient way to reduce important spatiotemporal dynamics in user mobility into a few eigen-behavior vectors. This also facilitates nodes to exchange their mobility summaries and determine their mutual similarity locally. Without any assumption on the properties of user population, we use unsupervised learning (clustering) techniques to classify WLAN users. Such a user grouping scheme based on learned user behavior is crucial for applications relying on the usage context of each mobile device (e.g., participatory sensing, social-relationship-aware message forwarding). In this study, using our systematic TRACE approach, we analyze wireless users' behavioral patterns by extensively mining wireless network logs from two major university campuses to showcase its efficacy. While our findings partly validate intuitive repetitive behavioral trends and user grouping, it is surprising to find the qualitative commonalities and striking consistency of user behavior from the two universities. We discover multimodal user behavior for more than 60 percent of the users, and there are hundreds of distinct groups with unique behavioral patterns in both campuses. The sizes of the major groups follow a power-law distribution.

Impact of culture on psychiatric practice

Introduction Mental illnesses are prevalent in all societies; however, the approaches to them differ from one society to another. The variation among cultures is a major cause of such differences. Culture refers to the unique behavior patterns and lifestyle shared by a group of people that distinguish it from other groups. A culture is characterized by a set of views, beliefs, values, and attitudes. Culture shapes attitudes, stereotypes, perception, emotions, way of thinking, imagination, and the way of living among individuals in each population. It is reflected in aspects such as common sayings, legends, drama, art, philosophical thought, and religions. Culture shapes people’s behavior, but at the same time, it is molded by the ideas and behavior of the members of the culture. Thus, culture and people influence each other reciprocally and interact continuously [1].

Investigating Commute Mode and Route Choice Variability in Jakarta using multi-day GPS Data

Traffic congestion has become a part of commuters’ life in Jakarta for several years. Even though 3-in-1 traffic regulation has been implemented since 1992 in order to reduce the number of car driver travelling in busy corridors during morning and evening peak hours, and Bus Rapid Transit (BRT) has been operated since 2004, which is aimed to attract car drivers to use public transport, the traffic congestion problem in Jakarta has not been solved. The condition is even predicted to worse if the transport facilities in Jakarta are not improved. In order to find effective measures for reducing car use and improving public transport attractiveness in Jakarta, better understanding of commute mode and route choice behavior would be advantageous. This paper reports the first results of data analysis regarding dynamic behavior of commuters’ mode and route choice in Jakarta. The data were collected using GPS devices including questionnaire sheets during a one-week period. 93 commuters participated in the survey. Even though commute trips are routine trips and therefore often assumed to be static, the results show the presence of dynamic behavior in choosing both modes and routes for commuting. The dynamic behavior is as a way to avoid traffic congested roads and 3-in-1 corridors, and to maintain trip-chaining activities/stops. Car drivers and motorcyclists change frequently their routes, especially during work-to-home trips. Motorcyclists were more dynamic in choosing their routes than car drivers. A unique pattern of mode and route choice behavior was found which can be used for developing mode and route choice model in Jakarta.