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

E-commerce has gained momentum with the rapid development of technology, and nowadays, we are permanently connected, with constant access to information and a wide range of products. Not only does a desktop computer offer us this possibility, but the latest-generation tablets and mobile phones create a broad framework. This paper investigates Romanian consumers’ attitudes towards adopting mobile technology for commerce (m-commerce), taking into account its development in the last few years, especially among younger generations. The main objectives of the research are to identify the preference for m-commerce use among Generation Z, establish the ways and the devices used by Gen Z individuals to inform about the products and services and order them, and analyze the factors influencing the use of m-commerce applications. The research methodology consists of conducting an empirical analysis using a distributed survey among youngsters from Generation Z in Romania. We used descriptive statistics, such as the analysis of frequency and the mean of variables, artificial neural network analysis (ANN), and multivariate analysis of variance (MANOVA), to validate the hypotheses. The research results indicate a solid inclination for m-commerce among Generation Z. The results are helpful for companies that can shape their marketing strategies to boost their sales using m-commerce channels among the younger population.

/pdf/assessing-the-adoption-of-mobile-technology-for-commerce-by-uapxnquw.pdf

Assessing the Adoption of Mobile Technology for Commerce by Generation Z

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