Application of the latent class regression methodology to the analysis of Internet use for banking transactions in the European Union

Guerrero, Mario; Egea, José Manuel Ortega; González, María Victoria Román

doi:10.1016/j.jbusres.2006.10.012

Cited by 42 publications

(9 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In other words, technologically based innovations appear to be a significant influence on the drivers of the adoption decision, and consequently, the structuring of the variables that explain the decision. This implication is important because it raises some reasonable concerns regarding the methodology employed when investigating consumer intention to adopt an innovation (e.g., Cheng et al., ; Grabner‐Kräuter and Faullant, ; Laukkanen, Sinkkonen, and Laukkanen, ; and Martínez Guerrero, Ortega Egea, and Román González, ). The use of longitudinal studies, compared with an ad hoc approach, will allow researchers to monitor the evolution from nonadopter to adopter, and consequently, will reveal more details of the mental progress that the consumer makes as he or she gains experience with the innovation.…”

Section: Discussion and Implicationmentioning

confidence: 99%

Adoption of Technologically Based Innovations: The Neglected Role of Bounded Rationality

Gounaris¹,

Koritos²

2012

J of Product Innov Manag

View full text Add to dashboard Cite

The purpose of this research is to examine the possibility of distinguishing between adopters and nonadopters when conceptualizing the drivers of the decision to adopt technologically based innovations. A second research objective is to examine factorial validity through the assessment of the explanatory power of the investigated conceptualization. In the pursuit of these objectives, the theory of bounded rationality represents the underlying theoretical framework, and Internet banking (IB) represents the nomological framework, in which two alternative conceptualizations, one for IB adopters and a second for nonadopters, are considered. “Intention to adopt” and “adoption” are the criterion variables, respectively. To meet the objectives of the study, two different populations are examined: adopters of IB and nonadopters. The former was used to examine the hypothesized framework for predictive validity against actual adoption; the latter was used to examine the predictive validity regarding intention to adopt. To collect data from IB adopters, the four leading banks, which account for approximately 73% of adopters, agreed to place a link to a Web‐based questionnaire at the log‐in page of their IB system inviting customers to participate in the study. Through this process, 858 useable questionnaires were produced. To reach the nonadopters population, a convenience sample of executive M.B.A. students from two leading Greek universities was employed. Respondents from this sample were screened to ensure that they had never used IB. This process yielded 418 useable questionnaires from the nonadopters population. A major finding from this investigation is that the decision to adopt improves the understanding of adopters regarding the benefits delivered by an innovation. Consequently, they hold a precise, less ambiguous perception of how specific innovation attributes translate into benefits. Hence, when recalling the decision process through which they adopted an innovation, adopters relate specific innovation attributes, including specific benefits received. This situation is displayed in the ability of a direct, first‐order model to capture the relationships between specific innovation attributes and the adoption decision. In contrast, nonadopters, having no direct experience with the innovation, lack this familiarity. They require a significantly greater amount of information in order to associate innovation attributes with potential benefits. The intangibility of technologically based service innovation further increases a nonadopter's need for information. However, this increased need for information renders nonadopters subject to cognitive strain, which causes them to aggregate innovation attributes into more abstract constructs. That aggregation was displayed in the ability of a second‐order model to capture the relationships between specific innovation attributes and the nonadopters' intention to adopt the innovation in the future. In both occasions though, the instrumental drivers of adoption represent the most...

show abstract

Section: Discussion and Implicationmentioning

confidence: 99%

Adoption of Technologically Based Innovations: The Neglected Role of Bounded Rationality

Gounaris¹,

Koritos²

2012

J of Product Innov Manag

View full text Add to dashboard Cite

show abstract

“…In a meta‐analysis of 22 different studies that classified users into internet user profiles taking into account the frequency of use, the variety of use and content preferences, Brandtzaeg (2010) proposed a media‐user typology (MUT), in which eight types of media users were identified: (1) Non‐Users , (2) Sporadics , (3) Debaters , (4) Instrumental Users , (5) Entertainment Users , (6) Lurkers , (7) Socializers , and (8) Advanced Users . Focused on banking transactions in the EU, Martínez Guerrero et al (2007) identified five types of European internet users: Laggards , mostly found in France, Germany and Ireland; Confused and adverse , mainly found in the United Kingdom and Austria; Advanced Users , mostly found in the Nordic countries, the United Kingdom and the Netherlands; Followers (frequent users of the internet, but not on a daily basis) mainly found in the Netherlands and Denmark; and Non‐Internet Users mostly found in Greece, Italy, Portugal and Spain. Based on data retrieved from the European Community Household Panel (ECHP), Brandtzaeg et al (2011) identified five types of internet users: Non‐Users , Sporadic Users , Entertainment Users , Instrumental Users and Advanced Users .…”

Section: Digital Divide In the Eumentioning

confidence: 99%

Is there a Common Digital Market in the European Union? Implications for the European Digitalization Strategy

Gomes

Dias

2022

J of Common Market Studies

View full text Add to dashboard Cite

Due to the impact of the COVID-19 pandemic, people has changed the way they work, learn and socialize. As result, it is important to identify the pre-existing digital gaps to implement the European Union digitalization strategy. This study aims to identify typologies of internet use in the 28 European Union (EU) countries (at the time of the survey), based on the characteristics of the users and their internet usage patterns. A two-level latent class analysis was applied. At the first level, individuals within each country were grouped according to their characteristics of internet use; and, simultaneously, at the second level, countries were grouped based on the similar structure of individual segments. Using data from Eurobarometer, results show that internet use in the EU digital market is not homogeneous. The European Commission should take these pre-existing gaps into account in the EU digitalization strategy.

show abstract

“…The Bayesian Information Criterion (BIC) is the most widely used goodness‐of‐fit measure for assessing LCCA models (Garver, Williams, and Taylor 2008; Vermunt and Magidson 2005). Typically, a model with a lower BIC value is preferred over one with a higher value (Guerrero, Egea, and Gonzales 2007).…”

Section: Review Of Motor Carrier Selection Literaturementioning

confidence: 99%

Carrier Selection:

Williams

Garver

Taylor

2013

Transportation Journal

View full text Add to dashboard Cite

There is a substantial body of research devoted to the processes shippers use in selecting motor carriers. Using data collected from 222 less-than-truckload (LTL) shippers, the current study attempts to further extend knowledge in this area in three ways by (1) examining additional carrier selection variables that heretofore have not been investigated, (2) employing a research method that has not been used in previous studies, and (3) conducting segmentation analyses of LTL shippers in their selection of motor carriers. In addition, this study identified five distinct need-based segments of LTL shippers that assigned differential importance to the variables considered in the selection process. The authors also describe the basic demographic characteristics of each segment. Recommendations for managerial actions and future research on carrier selection are provided.

show abstract

Application of the latent class regression methodology to the analysis of Internet use for banking transactions in the European Union

Cited by 42 publications

References 25 publications

Adoption of Technologically Based Innovations: The Neglected Role of Bounded Rationality

Adoption of Technologically Based Innovations: The Neglected Role of Bounded Rationality

Is there a Common Digital Market in the European Union? Implications for the European Digitalization Strategy

Carrier Selection:

Contact Info

Product

Resources

About