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In recent years, with the steady growth of China’s economy and world’s vacation market, and powered by the growing and significant large demands of Chinese overseas travel, an emergent trend of international development by major Chinese tourism groups has attracted notice by scholars and practitioners and this is obvious especially in the private sector. With this as the background, this paper aims to explore how China’s leading tourism companies expand their business internationally through a case study approach.

The purpose of this paper is to address the following question: Can a bank capitalize on its well-established self-service technologies (SSTs) in order to entice customers to adopt a newly introduced SST, namely, mobile banking? More specifically, it proposes an integrative model that simultaneously investigates the transference effects of attitudes, trust and the contagious influences of social pressures on mobile banking adoption intentions.

Structural equation modeling is applied to data collected from banks’ clients who are actually non-users of mobile banking.

The results indicate that attitude toward and trust in mobile banking along with coercive, normative and mimetic pressures are key antecedents to mobile banking adoption intentions. In addition, attitudes toward automated teller machines (ATMs) and online banking significantly predict attitude toward mobile banking. The results also support the effects of trust in ATMs as well as trust in online banking on trust in mobile banking. Moreover, predicted differences in the relative effects of attitude and trust are supported. Particularly, attitude toward online banking has a stronger impact on attitude toward mobile banking compared to the impact of attitude toward ATMs. In the same vein, the effect of trust in online banking on mobile banking is significantly stronger than the effect of trust in ATMs.

The study’s results hint at some practical and worthwhile guidelines for banks that can be leveraged in communication campaigns aiming at boosting the adoption rates of mobile banking. Banks can take advantage of the transference effects of the established attitudes toward and trusting beliefs in their mature SSTs as well as the contagious social influences in inducing the adoption of a newly introduced SST.

The present study represents a first step toward generating new insights into the role of the joint effects of attitudes, trust and social influences in the adoption of a new SST.

This study aims to explore the innovative strategies of business model of the free-to-fee switch, the relationship between the business model innovation and customer knowledge and further develop a conceptual model.

This study adopts a multiple case study method with abductive research logic, following the replication logic to select samples. A total of eight outstanding companies with altogether 312 free-to-fee switch events were selected from 1998 to 2021.

A strategic matrix with four innovative business models for the free-to-fee switch is generated. The parallelism between the models and customer knowledge orientations is also found. Further, the study develops the conceptual model regarding customer knowledge orientation as a key mediation.

The study highlights the conceptualization definition of customer knowledge orientation and its mediation effect to the business model innovation of free-to-fee switch, which is a new issue compared with previous research. Furthermore, it reveals that there exists organizational ambidexterity, which brings a new definition of customer knowledge orientation.

This study suggests how to integrate customer knowledge orientations to support the marketing process of the business model of free-to-fee switch. It also proposes a specific mechanism to conduct the free-to-fee switch with the introduction of four innovative strategic models and eight evolutional paths.

This study creatively proposes the strategic matrix and the conceptual model of business model innovation of free-to-fee switch. Moreover, a new conceptual definition of customer knowledge orientation is specified.

This study explores whether a new machine learning method can more accurately predict the movement of stock prices.

This study presents a novel hybrid deep learning model, Residual-CNN-Seq2Seq (RCSNet), to predict the trend of stock price movement. RCSNet integrates the autoregressive integrated moving average (ARIMA) model, convolutional neural network (CNN) and the sequence-to-sequence (Seq2Seq) long–short-term memory (LSTM) model.

The hybrid model is able to forecast both linear and non-linear time-series component of stock dataset. CNN and Seq2Seq LSTMs can be effectively combined for dynamic modeling of short- and long-term-dependent patterns in non-linear time series forecast. Experimental results show that the proposed model outperforms baseline models on S&P 500 index stock dataset from January 2000 to August 2016.

This study develops the RCSNet hybrid model to tackle the challenge by combining both linear and non-linear models. New evidence has been obtained in predicting the movement of stock market prices.

This study aims to explore how online reviews and users’ social network centrality interact to influence idea popularity in open innovation communities (OICs).

This study used Python to obtain data from the LEGO Innovation Community. In total, 285,849 reviews across 4,475 user designs between March 2019 and March 2021 were extracted to test this study’s hypotheses.

The ordinary least square regression analysis results show that review volume, review valence, review variance and review length all positively influence idea popularity. In addition, users’ in-degree centrality positively interacts with review valence, review variance and review length to influence idea popularity, while their out-degree centrality negatively interacts with such effects.

Drawing on the interactive marketing perspective, this study employs a large sample from the LEGO community and examines user design and idea popularity from a community member’s point of view. Moreover, this study is the first to confirm the role of online reviews and user network centrality in influencing idea popularity in OICs from a social network perspective. Furthermore, by integrating social network analysis and persuasion theories, this study confirms the interaction effects of review characteristics and users’ social network centrality on idea popularity.

This study’s results highlight that users should actively interact and share with reviewers their professional product design knowledge and/or the journey of their design to improve the volume of reviews on their user designs. Moreover, users could also draw more attention from other users by actively responding to heterogeneous reviews. In addition, users should be cautious with the number of people they follow and ensure that they improve their in-degree rather than out-degree centrality in their social networks.

This study integrates social network analysis and persuasion theories to explore the effects of online reviews and users’ centrality on idea popularity in OICs, a vital research issue that has been overlooked.