A commuting spectrum analysis of the jobs–housing balance and self-containment of employment with mobile phone location big data

2017 ◽  
Vol 45 (3) ◽  
pp. 434-451 ◽  
Author(s):  
Xingang Zhou ◽  
Anthony GO Yeh ◽  
Weifeng Li ◽  
Yang Yue
Keyword(s):  
Big Data ◽  
Mobile Phone ◽  
Southern China ◽  
The Self ◽  
Tertiary Sector ◽  
Individual Level ◽  
Location Data ◽  
Secondary Sector ◽  
Journey To Work ◽  
The Relationship

Studies on the jobs–housing balance and self-containment of employment are mainly focused on observed journey-to-work trips using travel survey data. This study examines the relationship between the jobs–housing balance and the self-containment of employment through the use of mobile phone location data in Shenzhen, a megacity in southern China. Individual-level journey-to-work trips are explored based on mobile phone location big data. Self-containment of employment in the suburban districts is higher than that in the central districts. The effect of the jobs–housing balance on self-containment of employment is examined at a 2 km grid level. Jobs–housing balance policies positively affect the self-containment of employment in the suburban districts, but its effect is limited in the central districts. Two extreme commuting spectrum measures are used to analyze self-containment of employment in different journey-to-work scenarios with the same jobs–housing distribution. Workers are disaggregated into secondary and tertiary sector workers according to job types. The self-containment of employment is found to be mainly affected by the local jobs–housing balance for secondary-sector workers and the regional city level job distribution for tertiary-sector workers. The extreme scenarios of commuting behavior using the commuting spectrum method can provide benchmarks that can help to understand the observed self-containment of employment better.

An Introduction, Review, and Conceptual Analysis of Mattering as an Essential Construct and an Essential Way of Life

2021 ◽  
pp. 073428292110576
Author(s):  
Gordon L. Flett
Keyword(s):  
The Self ◽  
Future Research ◽  
Way Of Life ◽  
Individual Level ◽  
Societal Level ◽  
Current Article ◽  
The Individual ◽  
The Relationship ◽  
Sense Of Mattering ◽  
Extended Discussion

While the importance of having self-esteem is widely recognized and has been studied extensively, another core component of the self-concept has been relatively neglected—a sense of mattering to other people. In the current article, it is argued that mattering is an entirely unique and complex psychological construct with great public appeal and applied significance. The various ways of assessing mattering are reviewed and evidence is summarized, indicating that mattering is a vital construct in that deficits in mattering are linked with consequential outcomes at the individual level (i.e., depression and suicidal tendencies), the relationship level (i.e., relationship discord and dissolution), and the societal level (i.e., delinquency and violence). Contemporary research is described which shows that mattering typically predicts unique variance in key outcomes beyond other predictor variables. Mattering is discussed as double-edged in that mattering is highly protective but feelings of not mattering are deleterious, especially among people who have been marginalized and mistreated. The article concludes with an extended discussion of key directions for future research and an overview of the articles in this special issue. It is argued that a complete view of the self and personal identity will only emerge after we significantly expand the scope of inquiry on the psychology of mattering.

scholarly journals A big data analysis of the relationship between future thinking and decision-making

2018 ◽  
Vol 115 (8) ◽  
pp. E1740-E1748 ◽  
Author(s):  
Robert Thorstad ◽  
Phillip Wolff
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Population Level ◽  
Future Thinking ◽  
Individual Level ◽  
The Future ◽  
The Individual ◽  
Near Future ◽  
The Relationship ◽  
Far Future

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people’s thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people’s tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people’s tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

Empires within and without: the conquest of the self and the Florentine avant-garde

Modern Italy ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 49-62
Author(s):  
Bertrand Marilier
Keyword(s):  
The Self ◽  
Individual Level ◽  
Avant Garde ◽  
Psychological Understanding ◽  
The Subject ◽  
The Individual ◽  
Intellectual Formation ◽  
Relationship Of ◽  
The Relationship ◽  
Intense Debate

This article examines the relationship of the young Giovanni Papini to the notion of imperialism. The period of Papini's intellectual formation was a time of intense debate among the Italian intelligentsia concerning imperialism and its relationship to nation and culture. He joined the conversation with a distinctive interpretation of the idea, one that could at once make him heir apparent to the tradition of Umbertian nationalism, while also rejecting the positivist slant of his forebears. William James's porous conception of the subject and Papini's sense of his own fragmented subjectivity provided the ground for a psychological understanding of imperialism: one that relied on knowledge and appreciation, which translated into literature at the individual level, and into culture at that of the nation. Ultimately, however, disappointments abroad, the demands of nationalist politics, and Papini's own avant-garde posture, led him to abandon his intellectual empire in favour of a more concrete one.

scholarly journals Heterogeneity Matters: Predicting Self-Esteem in Online Interventions Based on Ecological Momentary Assessment Data

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Vincent Bremer ◽  
Burkhardt Funk ◽  
Heleen Riper
Keyword(s):  
Social Contact ◽  
Well Being ◽  
Self Esteem ◽  
The Self ◽  
Ordinal Scale ◽  
Individual Level ◽  
Patient Heterogeneity ◽  
Ecological Momentary ◽  
Ema Data ◽  
The Relationship

Self-esteem is a crucial factor for an individual’s well-being and mental health. Low self-esteem is associated with depression and anxiety. Data about self-esteem is oftentimes collected in Internet-based interventions through Ecological Momentary Assessments and is usually provided on an ordinal scale. We applied models for ordinal outcomes in order to predict the self-esteem of 130 patients based on diary data of an online depression treatment and thereby illustrated a path of how to analyze EMA data in Internet-based interventions. Specifically, we analyzed the relationship between mood, worries, sleep, enjoyed activities, social contact, and the self-esteem of patients. We explored several ordinal models with varying degrees of heterogeneity and estimated them using Bayesian statistics. Thereby, we demonstrated how accounting for patient-heterogeneity influences the prediction performance of self-esteem. Our results show that models that allow for more heterogeneity performed better regarding various performance measures. We also found that higher mood levels and enjoyed activities are associated with higher self-esteem. Sleep, social contact, and worries were significant predictors for only some individuals. Patient-individual parameters enable us to better understand the relationships between the variables on a patient-individual level. The analysis of relationships between self-esteem and other psychological factors on an individual level can therefore lead to valuable information for therapists and practitioners.

Disparities of China’s regions development: dependence on the sectoral economic structure

2021 ◽  
Vol 71 (1) ◽  
pp. 84-95
Author(s):  
A.Yu. Zakharzhevskaya
Keyword(s):  
Statistical Data ◽  
Economic Structure ◽  
Tertiary Sector ◽  
Economic Disparities ◽  
Relative Contribution ◽  
Economic Level ◽  
Relative Decrease ◽  
Secondary Sector ◽  
The Relationship

The article explores the dynamics of changes in disparities of China’s regions’ economic level. According to a number of researchers, economic disparities between China’s regions started to decrease from about the mid-2000s. To clarify this picture the article uses indicator of contribution of the region’s GRP to the country’s total GRP. As a result of the research carried out by the author, it was found that in the PRC there really was a period when the economic gap between regions was narrowing down, but in general, changes in the relative contribution of regions to the country’s GRP are more complex than just a decrease or increase in economic disparities. Also, based on statistical data, the article draws conclusions about the relationship between the dynamics of the region’s contribution to the total GRP and the shares of the secondary and tertiary sectors in the region’s economy. It turned out that the increase in the economic level of the region in comparison with other regions is closely related to the share of the secondary sector in the GRP of this region: in most regions of China, the increase in the share of the secondary sector occurs in parallel with the growth of the contribution of the region’s GRP to the total GRP of the country. The growth in the share of the tertiary sector, on the contrary, in most cases is accompanied by a relative decrease in the economic level of the region, that is, its contribution to the total GRP decreases.

Can coaching leadership encourage subordinates to speak up? Dual perspective of cognition-affection

2019 ◽  
Vol 40 (4) ◽  
pp. 485-498 ◽  
Author(s):  
Chuqin Yuan ◽  
Yanfei Wang ◽  
Wenyuan Huang ◽  
Yu Zhu
Keyword(s):  
Affective Commitment ◽  
Southern China ◽  
Employee Voice ◽  
Voice Behavior ◽  
Content Type ◽  
Individual Level ◽  
Research Findings ◽  
Dual Perspective ◽  
Coaching Leadership ◽  
The Relationship

PurposeThe purpose of this paper is to explore the influencing mechanism of coaching leadership (CL) on employee voice behavior (VB) based on cognitive-affective system theory of personality (CAPS). Specifically, the study intends to build a model of psychological security (PS) and openness to change (OC) that mediate the relationship between CL and employee VB at an individual-level and group-level from cognitive-affective dual perspective.Design/methodology/approachCL, employee VB, PS and OC were assessed in an empirical study based on a supervisor–subordinate dyads sample of 287 employees and 72 team leaders from enterprises in Southern China.FindingsFrom CAPS theory perspective, the authors found that CL promotes employee VB and that PS and OC mediate the relationship between CL and VB.Practical implicationsResults underscore the importance of encouraging managers to engage in CL behaviors, which are conductive to enhancing employee PS and OC thereby improving employee VB. These results also highlight the significance of managerial attention to a secure voice atmosphere and the improvement of employees’ affective commitment to organizational change.Originality/valueThe research findings provide a significant contribution to the literature in that it shows PS and OC as crucial dual mediating mechanism through which CL influences VB. Moreover, this paper is one of the few studies answering the call to examine the effect of leadership at multiple levels.

scholarly journals An Application of K-Means Clustering on Tourist Activity in Maui Using Mobile Location Data

2021 ◽  
Author(s):  
Anna Meg Sheilds Brooker
Keyword(s):  
Big Data ◽  
Mobile Phone ◽  
Average Distance ◽  
Activity Patterns ◽  
Human Behaviour ◽  
Mobile Data ◽  
Mobile Location ◽  
Location Data ◽  
Tourism Management ◽  
Insight Into

Mobile location data are a major form of Big Data that hold many possibilities for study and insight into human behaviour. This research used mobile location data to investigate the differences in the activity patterns of tourists in Maui, Hawai’i. Mobile data used in this study were app-based location data collected as a stream of mobile phone locations with a timestamp. Tourists were clustered using K-Means based on time spent at attraction types. Different travel experiences were analyzed based on traveler’s accommodation choices, the average distance travelled from accommodation to attraction, and vacation length, which all varied significantly between the tourist clusters. This work provided a new use for K-means clustering with mobile location data to provide insightful information to marketing professionals and tourism management bodies.

Computational Approach for Personality Detection on Attributes

2020 ◽  
pp. 287-317
Author(s):  
Rohit Rastogi ◽  
Devendra Kumar Chaturvedi ◽  
Mayank Gupta
Keyword(s):  
Big Data ◽  
Linear Regression ◽  
Decision Tree ◽  
Computational Approach ◽  
The Self ◽  
Self Reflection ◽  
Human Behaviors ◽  
Aggressive Humor ◽  
Tree Regression Model ◽  
The Relationship

Psychologists seek to measure personality to analyze the human behavior through a number of methods, which are self-enhancing (humor use to enhance self), affiliative (humor use to enhance the relationship with other), aggressive (humor use to enhance the self at the expense of others), self-defeating (the humor use to enhance relationships at the expense of self). The purpose of this chapter is to enlighten the use of personality detection test in academics, job placement, group-interaction, and self-reflection. This chapter provides the use of multimedia and IoT to detect the personality and to analyze the different human behaviors. It also includes the concept of big data for the storage and processing the data that will be generated while analyzing the personality through IoT. Linear regression and multiple linear regression are proved to be the best, so they can be used to implement the prediction of personality of individuals. Decision tree regression model has achieved minimum accuracy in comparison to others.

scholarly journals An Application of K-Means Clustering on Tourist Activity in Maui Using Mobile Location Data

2021 ◽  
Author(s):  
Anna Meg Sheilds Brooker
Keyword(s):  
Big Data ◽  
Mobile Phone ◽  
Average Distance ◽  
Activity Patterns ◽  
Human Behaviour ◽  
Mobile Data ◽  
Mobile Location ◽  
Location Data ◽  
Tourism Management ◽  
Insight Into

Mobile location data are a major form of Big Data that hold many possibilities for study and insight into human behaviour. This research used mobile location data to investigate the differences in the activity patterns of tourists in Maui, Hawai’i. Mobile data used in this study were app-based location data collected as a stream of mobile phone locations with a timestamp. Tourists were clustered using K-Means based on time spent at attraction types. Different travel experiences were analyzed based on traveler’s accommodation choices, the average distance travelled from accommodation to attraction, and vacation length, which all varied significantly between the tourist clusters. This work provided a new use for K-means clustering with mobile location data to provide insightful information to marketing professionals and tourism management bodies.

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

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