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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.

This paper seeks to provide evidence that the long‐term success of capital‐intensive technology products requires continuous integration of innovations in the form of new features and capabilities that meet broad user preferences.

Magnetic resonance imaging (MRI) research centers, which represent lead users in this industry, are used as a case study. An online survey was developed to identify and rank the main factors behind brand switching, then secondary sources are used to confirm the research results.

A multi‐faceted approach to data collection is used to show that product innovations in the form of specific features are the main motive for switching to a new technology, consistent with the expectation that lead users seek technologies that maintain leading‐edge positions.

There are limitations to generalizing from this case study to other industries. The findings can be generalized to industries with similar characteristics, such as aircraft and heavy machinery manufacturing. In practice, managers should find a reliable strategy to assess factors underpinning brand switching that is unique to their industry. Determining the main factors behind switching is a critical matter when defining the appropriate strategy to keep their market share from eroding.

The literature reports considerable research that investigates brand switching. However, most of it focuses on highly competitive markets for consumer goods. This paper addresses a paucity of knowledge about what influences lead users of capital‐intensive products to switch between brands.

The purpose of this study is to determine the factors that underpin consumer switching intention in the smartphone industry. Most of the literature on brand switching uses conventional models that lack the ability to explain this behavior for high-technology products. Such products have unique characteristics that make the switching process more challenging from the consumer perspective.

The proposed model is built based on the related theories that consider the distinctive aspects of high-technology products. Furthermore, two variables “relative advantage of product features” and “company innovativeness” are introduced for the first time to evaluate consumer attitude to switch a high-technology product. The smartphone industry was selected to test the proposed model, where an online survey was sent to Apple and Samsung users.

The results confirm the expectation that perceived product usefulness, perceived ease of use and relative advantage of product features are the major factors driving the intention of users to switch, whereas subjective norms have limited impact. The financial cost of switching is the main barrier to consumers’ decision to switch to a new technology. The pleasure consumers feel toward their brand and the other brand is positively associated with their attitude toward switching.

This research contributes to the literature on brand switching by introducing a comprehensive model that explains consumer switching behavior of high-technology products. Research findings would allow managers to draft better marketing strategies to improve consumer brand awareness.

The majority of literature on brand switching uses simple models to explain consumer behavior. This study is the first attempt to build a comprehensive model that considers the characteristics of high-technology products and how they shape consumer behavior during the decision-making process.

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.

This study aims at identifying the most critical factors affecting the customer switching behavior for mobile service providers in Jordan. A number of 580 questionnaires distributed to a random sample of Jordanian mobile users. The questionnaire contains 33 items measured on a five‐point likert scale. The data were analyzed using regression analysis. It was found that all the independent variables (pricing, inconvenience, core service failures, service encounter failures, employee responsiveness to service failures, attraction by competitors, changes in technology, switching cost) had a significant effect on switching behavior of mobile service users except change in technology and employee responsiveness to service failure. Recommendations and directions for future research are proposed.

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.

The purpose of this paper is to investigate the factors that underpin consumer attitude toward switching a product brand, using functional magnetic resonance imaging (fMRI) to study brain activity during the decision-making process. Most of the literature shows that in the past, conventional marketing research approaches have been used to study brand switching among consumers. However, there is a lack of understanding of the importance of evaluating brain activations during the decision-making process when a consumer is selecting a brand.

The proposed model is a simplified version of consumer acceptance of technology model. This model accounts for cognitive and affect factors when choosing a product by including perceived usefulness and pleasure variables, respectively. An event-related fMRI experiment was designed and conducted using two smartphone brands.

The level of brain activation at the ventromedial prefrontal cortex (vmPFC) increased when participants were asked to judge images that reflect brand perceived usefulness compared with judging images that reflect brand pleasure. Similarly, the higher the perceived usefulness of the other smartphone, the greater the activation of the vmPFC during decision-making to switch to that smartphone.

This study contributes to the literature on brand switching by exploring the importance of fMRI technique in evaluating brain activities during decision-making to adopt a brand. For managers, research findings would allow them to draft better marketing and advertisement strategies that enhance consumer perception value of high technology brands and positive emotional experience.

Although the literature reports considerable research on brand switching, this is the first exploratory study to utilize fMRI to investigate consumer attitude toward switching. In addition, unlike most prior research, which uses generic products in fMRI studies, this study is utilizing high technology product to investigate the brand switching behavior.

The purpose of this paper is twofold: first, to clarify what specific behaviors are involved in consumers' partial switching in mobile application (app) usage, and, second, to explore the common and differential motivations of these behaviors.

This paper specified two behaviors in consumers' partial switching in mobile app usage, trialing and combining behaviors, and conceptualized them as different types of variety seeking behaviors. A theoretical model contrasting intrinsic motivations and extrinsic motivations on the two behaviors was developed and tested with a sample of 561 mobile app users in China.

The findings showed that both trialing and combining behaviors could be motivated by intrinsic individual-related and extrinsic technology-related factors. Besides, intrinsic individual-related factors were more effective in motivating trialing behavior, whereas extrinsic technology-related factors were more effective in motivating combining behavior. All these findings are applicable and consistent in both hedonic and utilitarian apps.

This study extends and advances the literature on information technology switching by investigating consumer use behaviors from a new perspective of partial switching and multiple competing apps usage. This study also contributes to variety seeking literature by extending the understanding of variety seeking to the context of mobile app usage. Finally, by investigating the associations and distinctions of trialing and combining behavior, this study not only helps to fully understand the partial switching but also enriches the understanding of different types of variety seeking behaviors.

This article provides a broad overview of telecommunications and network‐related technologies. Topics covered include identification and review of network elements, analog and digital signals, synchronous and asynchronous transmission formats, transmission media and equipment, transmission techniques and characteristics, multiplexing, network types, access technologies, network architectures and topologies, local‐area network technologies and attributes, protocols and protocol issues, gateways, internetworking, local networking alternatives, equipment certification, and various aspects of network management. It is intended to provide the practicing professional in the field of library and information science with a broad, up‐to‐date technical review that might serve to support and facilitate further investigation of current developments in networks and networking. Although the broad range of topics is not treated in depth, numerous references are provided for further investigation.