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The purpose of this paper is to explain the “good-to-good” app switching phenomenon that has not been specifically addressed in the prior switching literature. Drawing on the consumer learning theory, this study explores how external social word of mouth (WOM) and internal satisfaction influence app users’ switching intention through social learning route and analogical learning route. This study also examines the moderating effect of app heterogeneity.

An online survey was used to collect data. Two categories of mobile apps with different levels of within-category heterogeneity were targeted in survey questions. A total of 525 valid survey responses were collected.

Social WOM about a competing app increases users’ switching intention through both social norm influence and social information influence, resulting in a direct effect on switching intention and an indirect effect through the perceived attractiveness of a competing app. Users’ satisfaction with an adopted app positively influences the perceived attractiveness of an unadopted competing app, offering evidence for analogical learning in user switching. Meanwhile, users’ satisfaction imposes a direct negative effect on switching intention. A higher level of within-category heterogeneity strengthens (weakens) the positive effect of social WOM (satisfaction) on users’ perceived attractiveness of a competing app.

This study complements the existing switching literature by disentangling the “good-to-good” switching phenomenon in the mobile app market from the consumer learning perspective. This study extends the understanding of cross-category user switching by considering different levels of product heterogeneity.

This study aims to explore the switching behaviour of short video (SV) users and its influencing factors and promote the sustainable development of SV platforms (SVPs) and the marketing strategy formulation of library and information institutions.

Using the qualitative research method of semi-structured interviews and grounded theory, this study conducts an exploratory study on the user switching phenomenon of an SVP. The authors encoded the interview text at three levels, extracted the factors influencing user switching behaviour on an SVP and constructed the corresponding theoretical model.

This study identifies the following major internal and external factors influencing user switching behaviour of SVP: platform quality, social environment, individual characteristics and use needs. It also elaborates on the impact of these internal and external factors on user switching behaviour.

This study explored the factors influencing SV user switching behaviour and constructed corresponding theoretical models, enriching research in information technology and social media switching. In practice, this study helped the existing SVPs and library and information institutions establish a corresponding early warning mechanism to prevent the loss of existing users and attract new users.

During the past few years, social media has faced the challenge of maintaining its user base. Reports show that the social media giants such as Facebook and Twitter experienced a decline in their users. Taking WhatsApp's recent change of its terms of use as the case of this study and using the push-pull-mooring model and a configurational perspective, this study aims to identify pathways for switching intentions.

Data were collected from 624 WhatsApp users recruited from Amazon Mechanical Turk and analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The findings identify seven configurations for high switching intentions and four configurations for low intentions to switch. Firm reputation and critical mass increase intention to switch, while low firm reputation and absence of attractive alternatives hinder switching.

This study extends extant literature on social media migration by identifying configurations that result in high and low switching intention among messaging applications.

The study identifies factors the technology service providers should consider to attract new users and retain existing users.

This study complements the extant literature on switching intention that explains the phenomenon based on a net-effect approach by offering an alternative view that focuses on the existence of multiple pathways to social media switching. It further advances the authors’ understanding of the relevant importance of switching factors.

Given a product or service, the number of its installed user base has a significant positive effect on the existing users’ loyalty and new users’ conversion. This effect is conceptualized as network externalities in economics. Network externalities are supposed to be particularly striking in nowadays online business-to-business (B2B) platforms, but yet the mystery behind their effects on user loyalty to online B2B platforms remains to be delicately unraveled. The purpose of this paper is to discover the factors driving users’ loyalty, especially buyers’ loyalty, to online B2B platforms, by highlighting the impacts of network externalities on loyalty and other mediating factors.

A conceptual model of buyer loyalty under network externalities is elaborated. The reliability and validity of the instruments of the latent model constructs are assessed by confirmatory factor analysis, and the hypothesized causal relationships among the constructs are tested by structural equation modeling, on 710 valid buyer samples collected from a famous online B2B platform in China.

The analysis demonstrates that: perceived value, user satisfaction and switching costs are the major predictors of buyer loyalty to online B2B platforms characterized by network externalities; network externalities positively account for buyer loyalty by contributing to perceived value, user satisfaction and switching costs; and direct network externality (measured by perceived network size and perceived external prestige) has a significant effect on indirect network externality (measured by perceived compatibility and perceived complementarity).

The findings allow the authors to conclude meaningful managerial implications for online B2B service providers to build up loyal user bases through improving users’ perceptions of network externalities, switching costs and value.

Social networking sites (SNS) follow the same diffusion pattern and are subject to the same phenomena as other technologies (e.g. QWERTY keyboard, Microsoft Office and VHS) that were subject to increasing returns. Since they may lock-in users, increasing returns significantly alter the way a technology is used and should be managed. The purpose of this paper is thus to verify if SNS are subject to increasing returns and, if so, to better understand their impacts in this context.

A research model that combines path dependency theory (PDT) tenets with the push-pull-mooring (PPM) model of information technology (IT) switching was developed and tested with data collected from 416 SNS users via a field survey. Participants were voluntary students at a North American university enrolled in a compulsory undergraduate course in business administration. Partial least square analysis structural equation modeling (PLS-SEM) was used to validate our research model and test our hypotheses.

Results show that SNS are subject to three forms of increasing returns: those stemming from device complementarity, learning and adaptive expectations. In addition, the findings show that increasing returns stemming from SNS use have the potential to lock-in SNS users by increasing their switching costs.

SNS users should be careful when using an SNS since such use can create a path that is self-reinforced and that can lock them due to the increasing returns it yields. SNS vendors/providers need to learn how to manage increasing returns if they want to foster continued use of their SNS and/or poach users from their competitors. Lastly, SNS regulators should revise or put in place new governance mechanisms since increasing returns, when properly leveraged, may undermine fair competition by allowing companies to lock-in users and lock-out competitors.

This study contributes to IS research by: (1) empirically demonstrating that increasing returns are present in the context of SNS use, (2) identifying increasing returns as key antecedents of user switching costs, (3) validating a theoretical framework that allows for the appraisal of PDT tenets in a variance model and (4) instantiating PDT tenets at the individual level.

Most previous studies on new technologies and services have concentrated on their acceptance, seldom exploring in depth why users may choose not to accept technology or service and remain “non-users.” This study aims to understand free platform users' intention to switch to paid subscription platforms.

This study utilized push-pull-mooring (PPM) theory to investigate free OTT platform viewers' switching intentions toward paid OTT platforms. A research model was established and examined via a two-stage partial least square (PLS) method. A total of 446 free users were collected from Facebook and Line for data analysis.

Results show that perceived intrusiveness is the push factor and alternative attractiveness is the pull factor and that both have a positive impact on the switching intention of non-subscribers. Habit represents the mooring factor and negative affects switching intention. Perceived convenience and perceived enjoyment are shown to be two significant habitual antecedents. Furthermore, habit is revealed to moderate the effect of users' perceived advertisement intrusion and alternative attractiveness on switching intention to strengthen positive impact when the habit is strong.

This study is one of the pioneering studies to consider free-to-paid switching behavior on media services using PPM's structural equation model. Contrary to previous research, the study found that, in the context of the free-to-paid transition, highly accustomed users' perception of pull factors and push factors were strengthened, thus generating the tendency to switch platforms.

The purpose of this paper is to investigate the factors that underpin brand switching of medical imaging products by mass-market users. Most of the literature on brand switching is focused on competitive market products, for which switching costs are manageable. However, little consideration is given to brand switching of high-technology capital products.

The conceptual model is developed based on the existing literature on B2B brand switching. An online survey was developed and distributed to decision makers involved in purchasing medical imaging technology.

The results confirm the expectation that product features is the most influential factor underpinning brand switching. Product features are critical for medical organizations who want to maintain their competitive advantage. The findings suggest that the set of factors that influence the decision to switch is unique for users of different market segments in the same industry (e.g. lead users and mass-market users). This difference stems from technology utilization of each market segment.

In high-technology markets, managers should develop a reliable strategy to evaluate the antecedents behind brand switching that are specific to their industry. Knowledge of the major factors that cause users to switch is essential to allow firms to determine the strategy needed to prevent the erosion of their market share.

Although the literature reports considerable research on brand switching, this study is a first-of-its-kind in that it demonstrates that the factors underpinning brand switching vary within the same industry, based on the characteristics of each market segment. This paper develops new knowledge on the factors that influence the decision of users of high-technology capital products to switch between brands to renew or improve their internal capabilities.

The purpose of this paper is to explore the relationship between product innovativeness and the process of technology switching. This issue is important for two reasons: (1) in mature markets, the only way to increase market share is through consumers' switching from competitor firms and (2) it is essential to determine whether the product innovation strategy can meet users' needs in high-technology markets.

Research centers (university hospitals) specializing in magnetic resonance imaging (MRI) are the lead users of the MRI market. In this market, the technology switching process was tracked using an annual conference database. Interviews with industry experts and lead users were conducted in order to determine the relationship between product innovativeness and technology switching.

The findings reveal that in the lead users' segment, technology switching is occurring at a significant level. The interviews emphasized the influence of product innovativeness on technology switching in the global MRI market, as well as the importance of adopting an open innovation process as a strategy to enhance product innovativeness.

The results can be generalized to industries with similar characteristics, such as high rates of technological change and technology heterogeneity. In high-technology markets, managers should monitor switching behavior. They should also study the influence of product innovativeness on such behavior in order to determine the correct product innovation strategy and meet users' preferences effectively.

The literature reports considerable research that investigates switching behavior, but most publications use data from a short time period and cover a limited geographical region. This is the first study that uses data to track the switching behavior of high-technology products on a global scale over a 22-year period.

Smartphones have become a critical medium by which people remain in contact with family, friends, and colleagues. A variety of factors have contributed to the rapid prevalence of smartphones. The most influential factor is definitely the mobile platform or mobile operating system (OS). The purpose of this paper is to employ a theoretical framework based on an information systems success model and a theory values to examine the factors that affect smartphone users’ switching mobile OSs. Habit is regarded as a moderating variable to construct an integrated research model which helps researchers unveil the puzzle of users’ switching mobile OSs.

The proposed model was empirically evaluated using survey data collected from 424 users on their perceptions of smartphones. A structural equation modeling was used to assess the relationships of the research model.

The results of the study have shown that users consider the perceived switching value and satisfaction arising from their behaviors when deciding whether to switch to another mobile OS. Quality characteristics, including information quality, system quality, and service quality, are the key factors determining people’s perceived switching value and satisfaction. The participants of the study were grouped by degree of habit. The effect on satisfaction was not significant in the high-habit subgroup. Nevertheless, it has been found that the influence of the perceived switching value was stronger in the low-habit subgroup than in the high-habit subgroup.

This study contributes to a theoretical understanding of factors that explain users’ intention to switch mobile OSs.

Emerging social networking sites (SNSs) are less advantageous than leading SNSs in attracting users. They might stand a better chance if they know what users want. The purpose of this paper is to study factors that urge Facebook users to switch to Instagram to reveal how latecomers in the SNSs circuit can win the hearts of users.

This study proposes an SNS switching framework that is adapted from the demographic Push-Pull (PP) migration model to investigate users’ switching intention. Structural equation modeling was applied to analyze the data collected from 260 Instagrammers who all had experience using Facebook before moving on Instagram.

Results show that socializing and system quality of the SNS negatively affect users’ switching intention, while attractiveness of the alternative, peer influence and critical mass do the opposite. Surprisingly, enjoyment is not associated with switching intention.

SNSs switching may not mean a complete abandonment of previous SNSs. In many occasions, users simply become less active in one SNS and more active in other SNSs. The PP migration model provides a useful tool to understand the patterns as well as competing forces that influence the migration of SNS users, pushing them away or pulling them to new alternative sites. Specifically, pulling demonstrates to be a stronger influence than pushing.

This study suggests that SNS operators should satisfy users’ needs for socializing, maintain high system quality, provide peer influence tools and create their own attractive features, in order to retain existing customers or induce new users to switch.

This is one of the earlier empirical studies to investigate users’ switching intention from Facebook to Instagram with a valid sample. In addition, the present study approaches pull and push effects by multiple constructs, providing a clearer picture of what constitutes the pull and push forces.