Strong Path Research Articles

Unraveling the mystery of urban expansion in the Guangdong-Hong Kong-Macao Greater Bay Area: Exploring the crucial role of regional cooperation

Existing scholarship extensively explores the dynamics, determinants, and consequences of urban expansion, yet there is scant literature examining the impact of regional cooperation upon the directions and spatial forms of urban expansion amidst the fast-urbanizing process. This study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a developed megacity-region in southern China, to probe whether the notable urban expansion observed in contemporary China has been profoundly influenced by collaborative efforts among jurisdictions. Through the spatial metrics and panel data regression spanning the period from 2010 to 2018, this study unveils that regional cooperation has extended from coastal cities towards hinterland cities within the GBA. Consequently, urban land in most cities has undergone expansion in diverse directions. Furthermore, in contrast to economic and social cooperation, regional institutional cooperation emerges as the most influential factor driving external urban expansion. Additionally, heterogeneous results reveal that regional cooperation drives the external expansion of ordinary cities towards core cities. In contrast, the inertia within the urban system demonstrates strong path dependence on the pattern of adjacent expansion, contrasting with the external expansion facilitated by regional cooperation. In summary, this study illuminates the genesis and dynamics of urban expansion amid the city-regionalization process, going beyond interpretations confined to the municipal scale.

Path-dependence of the Plio–Pleistocene glacial/interglacial cycles

We find strong path dependence in the evolution of the Plio-Pleistocene glaciations using CLIMBER-2 Earth System Model simulations from the mid-Pliocene to modern preindustrial (3 My-0 My BP) driven by a gradual decrease in volcanic carbon dioxide outgassing and regolith removal from basal ice interaction. Path dependence and hysteresis are investigated by alternatively driving the model forward and backward in time. Initiating the model with preindustrial conditions and driving the model backward using time-reversed forcings, the increase in volcanic outgassing back-in-time (BIT) does not generate the high CO2 levels and relatively ice-free conditions of the late Pliocene seen in forward-in-time (FIT) simulations of the same model. This behavior appears to originate from nonlinearities and initial state dependence in the carbon cycle. A transition from low-amplitude sinusoidal obliquity (~41 ky) and precession (~23 ky) driven glacial/interglacial cycles to high-amplitude ~100 ky likely eccentricity-related sawtooth cycles seen between -1.25 My and -0.75 My BP (the Mid-Pleistocene transition or "MPT") in FIT simulations disappears in BIT integrations depending on the details of how the regolith removal process is treated. A transition toward depleted regolith and lowered atmospheric CO2 levels are both required to reproduce the MPT.

Intergovernmentalism in a supranational field: France, Germany, and EU competition policy reform

Competition policy is one of the few truly integrated policy fields of the European Union (EU), with supranational actors like the European Commission having extensive competences. Scholars consider it to be a relatively stable policy domain, characterised by strong path dependencies, a solid anchoring in European primary law, and the pre-eminence of epistemic authority. However, in recent years, EU competition policy has undergone remarkable changes including merger control, projects of common European interest, and state aid. This article argues that France and Germany, the EU’s two largest member states with most financial resources, have been decisive in promoting and realising these changes. Competition policy is an unlikely case for Franco-German European-level political work, primarily because of the supranational character of the policy field and the two countries’ oftentimes opposing positions on aspects related to the European single market. Building on policy document analysis and expert interviews, the article shows how and why France and Germany, partly in confrontation and partly in alignment with the Commission, have re-shaped EU competition policy.

Knowledge Sharing Behavior Shaped by Organizational Climate, Social Network, Perception, and Achievement Motivation

To date, knowledge sharing commonly discussed just as a part of knowledge management. However, knowledge sharing as a behavior is imperative to be investigated and managed carefully at a firm level. This study was aimed to examine employee knowledge sharing behavior could be shaped by organizational climate, social network, individual perception on knowledge itself, and achievement motivation. Data collected from questionnaires filled by 121 respondents who work at a multinational Japanese company operating in Indonesia (PT MII). Path analysis was used to evaluate causal model among variables. Result indicates that achievement motivation acts well as an intervening variable influences knowledge sharing behavior. Organization climate has a strongest path among variables with good practices performed by a supervisor; corporate policy to deploy knowledge; a knowledgeable feedback and corrective actions; and an assignment with a considerable time to deadline. Employees perceived that sharing behavior encouraged first in the network, promoted and managed by the organization, and lastly as a personal initiative. Motivated employees sharing their knowledge for self’s empowered, a sense of self merit, and share first at the situation of immediate and necessity. Idea for a better work more often shared than to find solutions for instant actions, tacit knowledge tends to be shared when requested, self’s refined knowledge shared individually rather than at a workgroup, and still there are some reluctances of senior owners to contribute their precious tacit knowledge at once. Keywords: Knowledge Sharing Behavior, Organizational Climate, Social Network, Individual Perception, Achievement Motivation

Bricolage or breakthrough? Entrepreneurial responses to tourism development in a regional tourism destination

The Evolutionary Economic Geography (EEG) framework contributes to the study of tourism destination evolution by focusing on the various circumstances and events through which tourism destinations develop over long periods of time. Our research objective is to investigate how players in tourism destinations shape development pathways when they face stagnant or lock‐in situations. Applying the concepts of path dependence and path creation, we explain how path shaping mechanisms such as bricolage (the process of combining available resources to create innovative outcomes) and breakthrough (a process where actors attempt to generate dramatic outcomes to deviate from existing pathways) occur using two destinations in the two regencies of the Toraja region of Sulawesi, Indonesia, as a case study. Understanding cultural tourism destination pathways requires frameworks capable of interrogating ethno‐political structures and histories and assessing how they influence developmental pathways that generate regional transformations. Our investigation indicates: strong path dependence in tourism, due to cultural, political, and economic conditions, inhibits breakthrough development; that the strength of path dependence at a regional level strongly influences the path shaping processes at the firm level; and that a breakthrough developmental process in tourism does not exclude bricolage.

Network Embeddedness and Company Competitiveness

ABSTRACT The purpose of the paper is to create a research model which analyses the impact of companies’ network embeddedness on their competitiveness through the lenses of knowledge cooperation in the network, competitor orientation and knowledge-oriented leadership. The data was collected using telephone interviews with 283 managers at medium-high technology companies. The findings revealed two relatively strong path connections between network embeddedness and competitiveness: one through knowledge cooperation in the network and competitor orientation and the other through knowledge-oriented leadership. In revealing the interconnections between network embeddedness and competitiveness, this paper argues for an indirect influence of the former on the latter.

Improved biological neural network approach for path planning of differential drive agricultural robots with arbitrary shape

To improve the path planning ability of a differential drive agricultural robot with arbitrary shape, a novel path planning method based on improved biological neural dynamics approach is proposed. Taking a T-shaped robot as an example, its shape features at different orientations are described through kernel matrix rotation. The coordinates and orientation of the robot are used as neuron position parameters to construct a 3-D neural network, and the neuron state is determined by convolutional calculation. Neural connections are defined based on the translational and rotational motion properties of the robot. By subdividing the workspace network, more flexible rotation options for the robot are obtained. Then, biological neural dynamics is established to determine a stable neural activity landscape, and a collision-free path can be obtained by consecutively selecting the adjacent neuron with maximum activity. The two key factors to improve the path planning ability are the flexible rotation options of the robot in a grid workspace and the consideration of the interaction between the robot body and the surrounding obstacles. It is proved that the proposed approach can find a feasible path within the range of rational numbers. Finally, its strong path planning ability is demonstrated by several experiments in narrow and complex environments.

The European skill space: a cross-country analysis of path-dependent capability development

ABSTRACT This study investigates the skill structures of European countries and their transformations from the perspective of capability development. The constructed skill space illustrates the skill sets of European nations based on product space methodology by linking skill occupation and occupation–country data from 2011 to 2018. The results show that there are remarkable differences in skill structures among countries, and there is a strong path dependence in skill development. The findings suggest that skill convergence is unlikely to occur and that skill inequality among countries requires serious consideration.

Estimating bidirectional effects between social connectedness and mental health in adolescent students: Addressing biases due to endogeneity

Research on the bidirectional relationship between social connectedness and health/mental health in adolescents is scarce, with most studies on adults. Some of the existing studies exploited the availability of longitudinal data to provide evidence of the existence of a causal relationship, either from social connectedness to health or establish a bidirectional relationship. There are at least two weaknesses associated with earlier research to assess the size of the effects. As acknowledged in the literature, one relates to attributing causality to empirical findings, due to well-known but inadequately addressed endogeneity biases. The other relates to failure to account for potentially important covariates, sometimes due to data limitations, or because such variables are not frequently used in sociological research. Existing research predominantly finds that the strongest path is from social connectedness to health/mental health, with effect estimates modest in size. I followed a quasi-experimental strategy by modelling adolescent students’ perceptions of social connectedness and mental health perceptions as potentially endogenous variables when estimating bidirectional effects. An instrumental variables (IV) modelling approach was followed, supplemented with a recently developed alternative approach to testing the exclusion restrictions of individual instruments. I exploited the rich information available in the PISA 2018 multi-country dataset, which allows for conditioning for a wide array of information on adolescent students’ personal circumstances, self-reported personality-related attributes, relationships with parents; and school characteristics. I found that (1) accounting for endogeneity biases is important; and (2) as opposed to findings reported in the literature, the dominant effect is from mental health perceptions to social connectedness for both male and female participants. The policy relevance of the findings is that adolescent mental health should be the primary focus of interventions, i.e., identifying and treating mental health symptoms as a primary intervention and as a precursor to improving the social connectedness of adolescents.

Analysis of the Significance of Life Cycle Theory in Urban Sustainable Development - Case Study of Resource-dependent Cities

Taking resource-dependent cities as an example, because of their single industry and strong path dependence, they could be influenced by the life cycle more strongly. So, more attention should be paid to their decline stage and upgrading. When cities are in their development stage and maturity stage which seem to be prosperous, potential crises like urban disease also exist. After years of research, how does the urban life cycle make a great difference in the development of cities had been studied thoroughly. But there is seldom application of this theory to proactively avoid the crisis of urban decline. By contrasting two pairs of cases, this paper will illustrate different problems that cities with different development pattern or orientation may encounter. Failing in recognizing the coming of decline stage and making timely transitions, Flint and Detroit paid a heavy price. Conversely Beijing succeeded in tackling its environmental pollution in development stage kept it from stepping into decline stage. Pittsburgh s success in industrial upgrading also kept it from death stage. More attention should be attached to the life cycle theory in guiding cities sustainable development, especially industrial transformation, and urban regeneration.

Evaluation of clinical parameters and biomarkers in older, untreated mantle cell lymphoma patients receiving bendamustine-rituximab.

Mantle cell lymphoma (MCL) is clinically and biologically heterogeneous. While various prognostic features have been proposed, none currently impact therapy selection, particularly in older patients, for whom treatment is primarily dictated by age and comorbidities. Herein, we undertook a comprehensive comparison of clinicopathological features in a cohort of patients 60 years and older, uniformly treated with bendamustine and rituximab, with a median survival of >8 years. The strongest prognostic indicators in this cohort were a high-risk call by a simplified MCL international prognostic index (s-MIPI) (HR: 3.32, 95% CI: 1.65-6.68 compared to low risk), a high-risk call by MCL35 (HR: 10.34, 95% CI: 2.37-45.20 compared to low risk) and blastoid cytology (HR: 4.21, 95% CR: 1.92-9.22 compared to classic). Patients called high risk by both the s-MIPI and MCL35 had the most dismal prognosis (HR: 11.58, 95% CI: 4.10-32.72), while those with high risk by either had a moderate but clinically relevant prognosis (HR: 2.95, 95% CI: 1.49-5.82). A robust assay to assess proliferation, such as MCL35, along with stringent guidelines for cytological evaluation of MCL, in combination with MIPI, may be a strong path to risk-stratify older MCL patients in future clinical trials.

A novel three-value grid scheme and rescue path planning algorithm for building fire

The 0-1 grid method is commonly used to divide a fire building into fully passable and fully impassable areas. Firefighters are only able to perform rescue tasks in the fully passable areas. However, in an actual building fire environment, there are three types of areas: fully impassable areas (areas blocked by obstacles or with heavy smoke and fire), fully passable areas, and partially passable areas (areas without obstacles or fire, but with some smoke risk). Due to the urgency of rescue, firefighters can consider conducting rescue tasks in both fully passable and partially passable areas to save valuable rescue time. To address this issue, we propose a three-value grid method, which classifies the fire environment into fully impassable areas, fully passable areas, and partially passable areas, represented by 1, 0, and 0.5, respectively. Considering that the ACO algorithm is prone to local optimum, we propose an enhanced ant colony algorithm (EACO) to solve the fire rescue path planning problem. The EACO introduces an adaptive heuristic function, a new pheromone increment strategy, and a pheromone segmentation rule to predict the shortest rescue path in the fire environment. Moreover, the EACO takes into account both the path length and the risk to balance rescue effectiveness and safety. Experiments show that the EACO obtains the shortest rescue path, which demonstrates its strong path planning capability. The three-value grid method and the path planning algorithm take reasonable application requirements into account.

Talkin' Bout a Revolution? Institutional Change in the EU Recovery and Resilience Facility: The Case of Climate Policy

AbstractThe European Union (EU) post‐COVID‐19 investment and reform programme, the Recovery and Resilience Facility (RRF), has been hailed as novel and ambitious, both as a fiscal instrument and as a lever for accelerating progress towards EU climate commitments. Yet, its design also exhibits strong path dependency, drawing on existing processes and commitments. Adapting theories of institutional change and models of hard/soft governance, we argue that the RRF is an example of significant yet gradual change – of evolution rather than revolution – taking place via layering and conversion of existing frameworks, and alteration of their logics of action. We show how the RRF repurposes the European Semester and track continuity and change in climate policy, a key priority area. Our findings suggest that the literature on institutional change should give greater consideration to the interplay between layering and conversion as a mechanism of gradual yet transformative evolution.

Characteristics and Operations of Complex Fuzzy Graphs

In this paper, Complex Fuzzy Graph (CFG) analyzed and introduced new concepts in CFG such as Spanning CFG, Complete CFG, path, arc, length, connected, strongest path and weakest path of CFG. We derived some properties of self complementary CFG and defined the operations on direct product, Semi strong product and strong product of CFG. Derived Isomorphic CFG with example is given in this paper. Moreover we introduced density of the graph and balanced complex fuzzy graph.

Global indicators and AI policy: Metrics, policy scripts, and narratives

AbstractArtificial intelligence (AI) has become a global policy issue that is actively governed by international actors producing governance indicators. This article argues that despite the arguments about disruptions to governance and policy due to AI, the global rankings increasingly constitute a strong path dependence on AI policy, leading to conformity with existing policies and institutional practices of economic competitiveness. By analyzing the composition and data sources of global indices in competitiveness, innovation, human capital, and artificial intelligence, I will show how the global rankings now evolve by sharing data and concepts. Consequently, these metrics and related policy scripts promote the seeming continuity of current activities of global competitiveness. AI is discussed as a “revolution” but framed as a matter of “competitiveness,” “openness,” and “talent competition,” implying standard perceptions of economic competitiveness and innovation. There is also a narrative element in the policy script, as the future policies on AI are promoted with references to history that also project the past into the future. My article concludes that while path‐dependent policy indicators and related future narratives give a sense of orientation, they are problematic as they portray a seeming continuity of activities in times of disruptions, delimiting policy alternatives such as AI ethics.

Six Blind Men and an Elephant: Workaholism vs. Work-Engagement from the Big-Two Personality Perspective rather than the Big Five

Purpose – This study attempts to compare and contrast workaholism and work engagement in terms of their dispositional antecedents. Although both concepts are perceived as heavy work investment, workaholism is associated with negative consequences such as burnout, counterproductive behavior, work-family conflict, psychosomatic symptoms, and declining work performance. Work engagement, on the other hand, is associated with positive aspects that include superior performance, organizational commitment, organizational citizenship behavior, physical and mental health. To distinguish a workaholic from a work engaged employee, this study offers a bird’s eye view using the Big Two, the higher order traits of the Big Five. Design/Methodology/Approach – The study is conducted on a sample of 250 full-time teachers (male: 154, female: 96; mean age:33.38 years) who were working at a higher education institution or a K-12 school in Istanbul, Turkey. The response rate was 90.9%. The convenience sampling method was used in data collection procedures. The data obtained by the survey method were analyzed using the structural equation modeling and common method variance techniques. Finding – According to the results, stability was positively and significantly correlated with work engagement but negatively and significantly correlated with workaholism. Plasticity, on the other hand, was correlated strongly and positively with workaholism yet had no statistically significant correlation with work engagement. The negative and weak correlation between Stability and workaholism became a stronger path in the structural regression model, indicating the presence of a suppressor effect. Discussion – The results of this research reveal that if an organization prefers work engaged employees rather than workaholics, then during the selection process, the hiring decision makers should look for the trait Stability as well.

Spatiotemporal Dynamic Evolution and Its Driving Mechanism of Carbon Emissions in Hunan Province in the Last 20 Years.

Global warming caused by carbon emissions is an environmental issue of great concern to all sectors. Dynamic monitoring of the spatiotemporal evolution of urban carbon emissions is an important link to achieve the regional "double carbon" goal. Using 14 cities (prefectures) in Hunan Province as an example, based on the data of carbon emissions generated by land use and human production and life, and on the basis of estimating the carbon emissions in Hunan Province from 2000 to 2020 using the carbon emission coefficient method, this paper uses the Exploratory Spatial-Temporal Data Analysis (ESTDA) framework to analyze the dynamic characteristics of the spatiotemporal pattern of carbon emissions in Hunan Province from 2000 to 2020 through the Local Indicators of Spatial Association (LISA) time path, spatiotemporal transition, and the standard deviation ellipse model. The driving mechanism and spatiotemporal heterogeneity of urban carbon emissions were studied by using the geographically and temporally weighted regression model (GTWR). The results showed that: (1) In the last 20 years, the urban carbon emissions of Hunan Province have had a significant positive spatial correlation, and the spatial convergence shows a trend of first increasing and then decreasing. Therefore, priority should be given to this relevance when formulating carbon emission reduction policies in the future. (2) The center of carbon emission has been distributed between 112°15'57″~112°25'43″ E and 27°43'13″~27°49'21″ N, and the center of gravity has shifted to the southwest. The spatial distribution has changed from the "northwest-southeast" pattern to the "north-south" pattern. Cities in western and southern Hunan are the key areas of carbon emission reduction in the future. (3) Based on LISA analysis results, urban carbon emissions of Hunan from 2000 to 2020 have a strong path dependence in spatial distribution, the local spatial structure has strong stability and integration, and the carbon emissions of each city are affected by the neighborhood space. It is necessary to give full play to the synergistic emission reduction effect among regions and avoid the closure of inter-city emission reduction policies. (4) Economic development level and ecological environment have negative impacts on carbon emissions, and the population, industrial structure, technological progress, per capita energy consumption, and land use have a positive impact on carbon emissions. The regression coefficients are heterogeneous in time and space. The actual situation of each region should be fully considered to formulate differentiated emission reduction policies. The research results can provide reference for the green and low-carbon sustainable development of Hunan Province and the formulation of differentiated emission reduction policies, and provide reference for other similar cities in central China.

Effect of Daily Life Reward Loop Functioning on the Course of Depression

Engagement in activities increases positive affect (Reward Path 1), which subsequently reinforces motivation (Reward Path 2), and hence future engagement in activities (Reward Path 3). Strong connections between these three reward loop components are considered adaptive, and might be disturbed in depression. Although some ecological nomentary assessment (EMA) studies have investigated the cross-sectional association between separate reward paths and individuals’ level of depression, no EMA study has looked into the association between individuals’ reward loop strength and depressive symptom course. The present EMA study assessed reward loop functioning (5x/day, 28 days) of 46 outpatients starting depression treatment at secondary mental health services and monitored with the Inventory of Depressive Symptomatology—Self-Report (IDS-SR) during a 7-month period. Results of multilevel regression analyses showed significant within-person associations for Reward Path 1 (b = 0.21, p < .001), Reward Path 2 (b = 0.43, p < .001), and Reward Path 3 (b = 0.20, p < .001). Stronger average reward loops (i.e., within-person mean of all reward paths) did not relate to participants’ improvement in depressive symptoms over time. Path-specific results revealed that Reward Paths 1 and 2 may have partly opposite effects on depressive symptom course. Together, our findings suggest that reward processes in daily life might be best studied separately and that further investigation is warranted to explore under what circumstances strong paths are adaptive or not.

THE USE OF ROBOTS FOR DELIVERY OF PACKAGES IN FOOD INDUSTRIES AND ITS IMPACT ON JOB LOSS

Artificial intelligence (AI) and robotics have developed rapidly in the last few years, both in terms of the resources and outputs they produce. The robots that work in the food industry contribute significantly to the transportation of food packages from one location to another. The main task of the robots in the food industry on which this research focuses is delivery of packages. Before the implementation of robots in food industries and in delivery packages, it was done by human beings. Now that the robots are utilised, human beings will lose their jobs. This might not necessarily be the case or there might be some unforeseen issues. That is why this research aims to investigate the influence of system quality, information quality, and business value on the delivery of packages by robots in replacing people's jobs. This study applied a quantitative research method in order to achieve all of the research objectives. A total of 310 participants took part in the survey. Based on PLS-SEM analysis, the path coefficient of system quality to business value was examined by hypothesis one (H1), and it was shown to be supported. It is clear that the relationship between system quality and business value is significant because there is a strong link between system quality and business value. Furthermore, the path coefficient of information quality to business value was investigated in hypothesis two (H2).Our second hypothesis is supported by the p-value being significant and positive. Hypothesis three (H3) is significant, as evidenced by the fact that it is supported. As a result, there are important connections between the use of robots and business value. Finally, the business value, which is a dependent variable, has a positive and significant relationship with all independent variables of this research. There is a strong path coefficient link from business value to system quality, information quality, and the use of robots. In the measurement model, there are substantial disparities between the industries with high levels of working experience and those with less working experience of robots. Information quality, use of robots, and business value all have positive and significant influences on the use of robots in the food industry (delivery of packages by robots). Furthermore, the analyses of PLS-SEM also show that system quality has a positive relationship but not a significant impact. Technological skills are highly important in order to improve and adopt delivery of packages by robots in the food industry. In addition, the findings of this research contribute to the literature on robots’ implementation in the food industry and also contribute to limited empirical research on assessing the delivery packages by robots in food industries on replacing people's jobs.

Directed rough fuzzy graph with application to trade networking

In the realm of linking networks to the real world, connectivity (strength of connectedness) plays a crucial role. In this article, we introduce three types of vertices based on the indegree and outdegree of the vertices of directed rough fuzzy networks (DRFNs). We also define the concept of strength-reducing sets (mathcal {SRS}s) of DRF-vertices, DRF-edges, and important related results using the strongest path in directed rough fuzzy graphs (DRFGs). We generalize the idea of Menger’s theorem of vertices and edges in directed fuzzy graphs to directed rough fuzzy graphs which are appropriate for dealing with uncertainty in information systems. Furthermore, we use alpha strong DRF-edges, beta strong DRF-edges and delta DRF-edges to identify developing countries most affected by trade deficits during COVID-19. Finally, our research results are compared with existing methods to demonstrate their applicability and productivity.