Multiscale GIS based-model to assess urban social vulnerability and associated risk: Evidence from 146 urban centers of Eastern India

The evolution of technology has become the mainstream of the current technological innovation era. Technological change is organized in its unique pattern and a new approach that takes place in a systematic and selective manner. Such change is generally molded with the amalgamation of various factors, namely, economic, social or scientific and technological. This paper aims to focus on identifying technological trajectories in a technological ecosystem with the case of m-payment technology.,This study constructs a patent citation network for mobile payment service technology through patent citation data and identifies the main evolution process using the main path analysis of the network. The scope of this study focuses on key innovation using social network analysis and patent citation network, validated using the case of a mobile payment system and analyzing its technological trajectory.,Analyzing technology evolution provides a greater insight of the overall technology landscape to the researcher and practitioner. Analyzing the m-payment technology landscape gives three main categories of m-payment systems: the mobile financial transaction system), the payee mobile device payment selection system and e-wallet services.,The novelty of this research lies in the process of identifying technological evolution using social network and patent citation network analysis. The case of m-payment technology ecosystem is studied quantitatively which is not explored by previous researchers. This research provides a way to develop the main path technology of innovative products or services to identify technology evolution using the case of m-payment landscape.

A structural analysis approach to identify technology innovation and evolution path: a case of m-payment technology ecosystem

The last decades have seen continuous increases in electronic commerce (e-commerce) and particularly mobile commerce (m-commerce). These sharp increases, especially during the COVID-19 pandemic, have led companies to become aware of the potential of this trade channel. This paper investigates the effects of antecedents on behavioral intention in m-commerce and the role of consumer satisfaction in the buyer decision process. In our investigation, we used the modified technology acceptance model (TAM). The research was conducted through a survey based on a self-administered questionnaire, with the data being analyzed by structural equation modeling and cross-tabulation. Following the investigation, we found that perceived usefulness (PU) and perceived ease of use (PEU) positively influence behavioral intention. Consumer satisfaction also plays a significantly positive role in m-commerce actual use, influencing future behavioral intention. The results also showed that generational and gender differences strongly affect behavioral intention, with younger generations and male respondents being more inclined to use m-commerce.

/pdf/assessing-antecedents-of-behavioral-intention-to-use-mobile-41z2wo5en3.pdf

Assessing Antecedents of Behavioral Intention to Use Mobile Technologies in E-Commerce

This study integrates the three-factor theory and Importance–Performance Analysis (IPA) into a three-dimensional importance–performance analysis (3-D IPA) approach to identify the critical service quality attributes for hotel online booking. A seven-point Likert-type scale of service quality measurement was designed in the survey and the participants (foreign independent tourists) were randomly selected at Taoyuan International Airport, Taiwan. A total of 453 participants were identified. The classification of the factors was based on the explicit importance, while the implicit importance was measured with the relationship of satisfaction by using the ordered probit model. The results, compared to the traditional method of partial correlation analysis, were different in the dimensions of Fulfillment and Responsiveness, Safety and Security, Website Functionality, and Customer Relationships. In conclusion, this study broadens the perspective of research method and improves the performance evaluation of e-service quality attributes. The empirical results provide recommendations and policy implications for resource allocation of hotel management.

https://www.mdpi.com/2071-1050/13/4/2043/pdf

Application of Revised Importance–Performance Analysis to Investigate Critical Service Quality of Hotel Online Booking

A bibliometric analysis and visualization of passive optical network research in the last decade

Smart tourism, also known as smart tourism, actively captures tourism activities, tourists, tourism economy, tourism resources, and other information through mobile Internet and mobile terminal Internet of things devices and emerging technologies such as cloud computing and Internet of things. In order to release the intelligent tourism information in time, let the masses know the information in time, and adjust the work and tourism plan in time, this paper proposes SM-PageRank algorithm and secondary ranking based on user interest model, in order to study the accuracy of tourism information retrieval. The methods used in this paper include the principle of three weighted information fusion algorithms, LBS technology, and the design of intelligent tourism system. The function of information fusion algorithm is to find the global optimal solution for travel routing. LBS technology collects real-time tourism information through some entity sensors. Through information retrieval experiment and fusion technology solution experiment, the results show that the SM-PageRank algorithm and the secondary sorting based on user interest model proposed in this paper improve the average accuracy by 20.1% compared with the traditional algorithm and 2.6% compared with Google search. The Internet of things fusion algorithm gives a line planning set with standard deviation of 0.4 for the set of travel days with standard deviation of 1.92.

/pdf/sm-pagerank-algorithm-based-user-interest-model-for-mobile-l4q0uehp.pdf

SM-PageRank Algorithm-Based User Interest Model for Mobile Smart Tourism Platform

Carrying out social vulnerability research has become an important way to understand the sustainable development of resources, the environment, populations, and societies. Clarifying the research context and development trend of social vulnerability is of great significance to the follow-up theoretical research on and practical exploration of sustainable social development. With the help of a CiteSpace knowledge map analysis, this study reveals the research hotspots and their evolution in different periods and puts forward the key problems in and future direction of social vulnerability research in the future. This study found that the number of articles on social vulnerability research showed a steady upward trend and that the research experienced roughly three stages: an embryonic stage, a development stage, and a stable stage. The United States, Brazil, the United Kingdom, and China accounted for the majority of the research, but the intensity of cooperation between them is still weak. Vulnerability assessment and risk assessment in the context of policy and environmental change are hot topics in the current research. In the future, it is necessary to focus on the comprehensive research on the integrated and cross-scale research on social vulnerability, research on its occurrence and evolution, and on the dynamic monitoring as well as optimal regulation of social vulnerability under multiple pressures.

/pdf/knowledge-domain-and-emerging-trends-of-social-vulnerability-3n1t8ie6.pdf

Knowledge Domain and Emerging Trends of Social Vulnerability Research: A Bibliometric Analysis (1991–2021)

With the advance of 5G communication technologies and Internet+ strategy, mobile commerce has experienced rapid growth and needs urgent attention from researchers. It is the aim of this article to analyze the literature on mobile commerce to address the following question: With the wide application of artificial intelligence and big data, what are the latest technology, models and problems in the background of the new era that researchers and practitioners need to understand in order to grasp the research frontier in this field quickly? Therefore, to achieve these objectives, this paper reviews 1130 m-commerce articles with 25,502 associated references from the SCI-EXPANDED, SSCI, CPCI-S, CPCI-SSH database and develops a framework of m-commerce value by analyzing the most influential authors, institutions, countries, journals and keywords in m-commerce. We apply three types of knowledge mapping to our study—cluster view, timezone view and timeline view. Frequency statistics, clustering coefficient as well as centrality calculation are employed to analyze by CiteSpace. We use the strength of citation bursts to analyze keywords and put result into the I-Modelwhich provide an important framework for classifying m-commerce activities and theories. In this study, we explore the knowledge structure, development and the future trend of mobile commerce for researchers. We identify the main technology and models to improve customer satisfaction and adoption behavior in the background of the new era which provide decision support for practitioners. Compared with the existing literature reviews of mobile commerce, we make a set of knowledge maps to show the future trend of mobile commerce and analyze visual results based on I-model. It is the first study to present the major clusters to reveal their associated intellectual bases and research fronts.

https://www.mdpi.com/2071-1050/11/6/1580/pdf

The Knowledge Mapping of Mobile Commerce Research: A Visual Analysis Based on I-Model

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Papers

SM-PageRank Algorithm-Based User Interest Model for Mobile Smart Tourism Platform

Knowledge Domain and Emerging Trends of Social Vulnerability Research: A Bibliometric Analysis (1991–2021)

The Knowledge Mapping of Mobile Commerce Research: A Visual Analysis Based on I-Model