Dynamic Use Diffusion Model in a Cross‐National Context: A Comparative Study of the <scp>U</scp>nited <scp>S</scp>tates, <scp>S</scp>weden, and <scp>I</scp>ndia

Shih, Eric; Venkatesh, Alladi; Chen, Steven; Kruse, Erik

doi:10.1111/j.1540-5885.2012.00982.x

Cited by 16 publications

(23 citation statements)

References 46 publications

(64 reference statements)

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“…For example, Shih and Venkatesh (2004) find that adopters with higher use diffusion levels are not only more satisfied with the current innovation but also more interested in adopting future innovations. Building on the use diffusion findings related to user groups and usage patterns, Shih et al (2013) contend that mere adoption of an innovation does not complete the diffusion process, because it does not guarantee that the product will be integrated into regular use in a meaningful way. The study also finds that although individual differences have a weak but significant impact on how technology usage evolves, the way people communicate with one another and the technological environment of the household play larger roles in the process.…”

Section: Conceptual Framework For Understanding Cultural Differences mentioning

confidence: 99%

Understanding Cultural Differences in Innovation: A Conceptual Framework and Future Research Directions

Kumar

2014

Journal of International Marketing

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Extant literature on innovation has produced important and significant results. However, no study to date has provided researchers with a framework to understand innovation from a cultural differences perspective. To fill this research gap, the author proposes a framework that categorizes culture and innovation studies into the following six approaches:(1) innovation characteristics, (2) (6) organizational functions. Each approach contains two perspectives. From these approaches and perspectives, the author identifies unique and general insights on culture and innovation, discusses the implications of implementing this framework, and recognizes possible areas of further research. adoption of/propensity to adopt innovations, (3) geographical innovations, (4) market characteristics, (5) learning effect, and

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Section: Conceptual Framework For Understanding Cultural Differences mentioning

confidence: 99%

Understanding Cultural Differences in Innovation: A Conceptual Framework and Future Research Directions

Kumar

2014

Journal of International Marketing

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“…In their study of the use-diffusion of personal computers within households, Shih and Venkatesh (2004, p. 60; see also Shih et al, 2013) defined variety of use as "the different ways the product is used." For example, in the case of home computers, the authors identified a variety of different uses, included work-related use, communication, entertainment, home management, home shopping, education and information gathering.…”

Section: Variety Of Pioneer Product Usesmentioning

confidence: 99%

“…This scale was based on computer-use activities identified in previous research (Robinson and Godbey, 1997;Venkatesh, 1996) and used in several subsequent studies (e.g. Shih et al, 2013; Variable Definition…”

Section: Questionnaire Developmentmentioning

confidence: 99%

“…In some cases, this approach may favor the internal development of some complementary products (Ende et al, 2013). In addition, pioneer firms can develop strategies to undermine the effectiveness of follower strategies that attempt to lower switching costs (Markides, 2006) and increase the number of ways a pioneer adopter uses a pioneer product (Shih et al, 2013).…”

Section: Practical Implicationsmentioning

confidence: 99%

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The impact of pioneer adopter characteristics and perceptions on the perceived costs of switching to a follower product

Parry

Sarma

2019

APJML

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Purpose The purpose of this paper is to propose and test a model in which the perceived post-purchase monetary costs and time costs of switching from a pioneer product are a function of the perceived difficulty of comparing follower products with the pioneer product, the variety of ways in which the pioneer product is used by an adopter, pioneer adopter satisfaction with the pioneer, the familiarity of the pioneer adopter with follower products and the anticipated reactions to switching of other household members who use the pioneer product. Design/methodology/approach The authors test this model with data collected from 518 Japanese iPad owners. Hypotheses are evaluated using structural equation modeling. Findings The authors find that each of the hypothesized independent variables is related in the hypothesized direction with one or both types of switching costs. Research limitations/implications Findings indicate that the variety of pioneer product use, the perceived negative reaction of other household users of the pioneer product and comparison difficulties between the pioneer and follower product have an important influence on the perceptions of the perceived costs of switching from a pioneer to a follower product. Practical implications Findings suggest that managers responsible for launching follower products can lower the perceived costs of switching from a pioneer product through specific product design and communication decisions. Originality/value In contrast with prior switching-cost research, this paper focuses on switching costs as perceived by pioneer adopters and examining the importance of pioneer-follower product comparison difficulties, the variety of pioneer product use and the negative reactions of other household users of the pioneer product.

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“…Anadarajan et al (2002) note that social pressure is critical in the behavior of technology users. Shih and Venkatesh (2003) examine home computer use in the United States, Sweden, and India and find a significant relationship between attitudinal belief and use outcome in the Indian sample. In other words, culture has an influence on technology adoption behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

Hospitality Industry Web-Based Self-Service Technology Adoption Model

Lee

2013

Journal of Hospitality & Tourism Research

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Technology advancement induces information technology infusion in business processesand service encounter. The airline industry employs web-based self-service technology (SST), namely, airline online check-in system, to provide more choice, control, and convenience to passengers. Customer adoption intention of web-based SST is particularly momentous, since customer adoption highly drives the service development. Technology acceptance model (TAM), a robust framework measuring factors affecting technology acceptance intention, has been broadly examined in numerous settings. However, inconsistent results are noted in Western and non-Western countries, and the model is challenged from limited cultural orientation. In response to this criticism, this research aims to identify culturally unique dimensions for TAM and construct a framework for hospitality web-based SST adoption from Westerns' and Asians' perspectives. Eticemic approach, incorporating literature search and focus group interviews with Asian respondents, was employed to provide a thoughtful review of examined factors and generate new factors from an Asian perspective.

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Dynamic Use Diffusion Model in a Cross‐National Context: A Comparative Study of the United States, Sweden, and India

Cited by 16 publications

References 46 publications

Understanding Cultural Differences in Innovation: A Conceptual Framework and Future Research Directions

Understanding Cultural Differences in Innovation: A Conceptual Framework and Future Research Directions

The impact of pioneer adopter characteristics and perceptions on the perceived costs of switching to a follower product

Hospitality Industry Web-Based Self-Service Technology Adoption Model

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