Technophilia as a driver for using advanced traveler information systems

Abstract Advanced Traveler Information Systems (ATIS) provide comprehensive trip information for all modes of transport while considering the current traffic situation; however, impacts on travel choices are weak, which might be due to insufficient consideration of user characteristics. As a critical determinant of willingness to use, we propose and validate technophilia, an openness, interest and fascination towards information and communication technologies. Drawing on data from a survey of 1300 Austrians, we describe willingness to use ATIS, and delineate target groups by socio-demographic characteristics. We establish validity of a technophilia measure consisting of seven survey questions. All questions constitute a common factor (construct validity). The technophilia measure can be distinguished from social norms and general technology-related values (discriminant validity). Technophilia is more pronounced among men, younger people, individuals with higher education and persons who frequently use the Internet for travel information or who frequently use an in-car navigation system. Among a range of potential determinants, technophilia is verified as an independent determinant of willingness to use ATIS (criterion validity). The results suggest to pay particular attention to the technophilia dimension in ATIS user requirements. Technophiles may advocate ATIS in their social network. The applied seven questions provide a short and valid scale of technophilia which may contribute to customer segmentation or to explaining the acceptance of traveler information.

[1]  Jane Lappin,et al.  Users of a regional telephone-based traveler information system – a study of TravInfo™ users in the San Francisco Bay Area , 2000 .

[2]  Toni Ahlqvist,et al.  Is the transport system becoming ubiquitous? Socio-technical roadmapping as a tool for integrating the development of transport policies and intelligent transport systems and services in Finland , 2010 .

[3]  G. Lyons The role of information in decision-making with regard to travel , 2006 .

[4]  Cinzia Cirillo,et al.  Understanding variability, habit and the effect of long period activity plan in modal choices: a day to day, week to week analysis on panel data , 2014 .

[5]  J Lappin,et al.  TRAVELER RESPONSE TO INFORMATION: WHO RESPONDS AND HOW? , 2002 .

[6]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[7]  Thomas F. Golob,et al.  Structural Equation Modeling For Travel Behavior Research , 2001 .

[8]  S. Schwartz Normative Influences on Altruism , 1977 .

[9]  S. M. Chambers,et al.  Psychological and Situational Influences on Commuter-Transport-Mode Choice , 2005 .

[10]  Ortwin Renn,et al.  Wahrnehmung und Bewertung von Technik in Baden-Württemberg , 1998 .

[11]  G. Lyons,et al.  What affects pre-trip public transport information use? Empirical results of a qualitative study , 2008 .

[12]  Piet Rietveld,et al.  Public transport strikes and traveller behaviour , 2001 .

[13]  Deborah E. Rosen,et al.  Applying the Environmental Propensity Framework: A Segmented Approach to Hybrid Electric Vehicle Marketing Strategies , 2010 .

[14]  G. Roehrich Consumer innovativeness: Concepts and measurements , 2004 .

[15]  Hong Kian Sam,et al.  Computer Self-Efficacy, Computer Anxiety, and Attitudes toward the Internet: A Study among Undergraduates in Unimas , 2005, J. Educ. Technol. Soc..

[16]  G. Lyons,et al.  What Affects Use of Pretrip Public Transport Information? , 2008 .

[17]  G. Norman Likert scales, levels of measurement and the “laws” of statistics , 2010, Advances in health sciences education : theory and practice.

[18]  E. Molin,et al.  Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature , 2006 .

[19]  Steve W. Edison,et al.  Measuring attitudes towards general technology: Antecedents, hypotheses and scale development , 2003 .

[20]  Alan Durndell,et al.  Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample , 2002, Comput. Hum. Behav..

[21]  Nikolay Mehandjiev,et al.  The Impact of a Mobile Information System on Changing Travel Behaviour and Improving Travel Experience , 2013, MobiWIS.

[22]  Rocco J. Perla,et al.  Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes , 2007 .

[23]  D. Metz Peak Car and Beyond: The Fourth Era of Travel , 2013 .

[24]  Yu-Hsin Liu,et al.  Route switching behavior on freeways with the provision of different types of real-time traffic information , 2005 .

[25]  E. Rogers Diffusion of Innovations , 1962 .

[26]  B. Verplanken,et al.  Habit, information acquisition, and the process of making travel mode choices , 1997 .

[27]  Erfassung von Technikbereitschaft,et al.  Entwicklung und Validierung einer Kurzskala zur Erfassung von Technikbereitschaft , 2012 .

[28]  Barbara Lenz,et al.  Mobility information services and its consequences for travel behaviour considering different user types , 2010 .

[29]  J. Lappin,et al.  Comparative Analysis of Customer Response to Online Traffic Information in Two Cities: Los Angeles, California, and Seattle, Washington , 2004 .

[30]  Hani S. Mahmassani,et al.  DYNAMICS OF COMMUTING DECISION BEHAVIOR UNDER ADVANCED TRAVELER INFORMATION SYSTEMS , 1999 .

[31]  L. S. Newman,et al.  Increasing attitude-behavior correspondence by broadening the scope of the behavioral measure. , 1976 .

[32]  Dirk Wittowsky Dynamische Informationsdienste im ÖPNV : Nutzerakzeptanz und Modellierung , 2009 .

[33]  Said S. Al-Gahtani,et al.  Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology , 1999, Behav. Inf. Technol..

[34]  Anna Kramers,et al.  Designing next generation multimodal traveler information systems to support sustainability-oriented decisions , 2014, Environ. Model. Softw..

[35]  L. Stalker,et al.  Does Travel Information Influence Commuter and Noncommuter Behavior?: Results from the San Francisco Bay Area TravInfo Project , 1999 .

[36]  Tae-Gyu Kim,et al.  A Longitudinal Analysis of Awareness and Use for Advanced Traveler Information Systems , 2004, J. Intell. Transp. Syst..

[37]  Serge P. Hoogendoorn,et al.  Joint Modeling of Advanced Travel Information Service, Habit, and Learning Impacts on Route Choice by Laboratory Simulator Experiments , 2005 .

[38]  J. Garvill,et al.  Interrupting habitual car use : The importance of car habit strength and moral motivation for personal car use reduction , 2008 .

[39]  Pushpendra Singh,et al.  Using immersive video to evaluate future traveller information systems , 2007 .

[40]  Nikos Bozionelos,et al.  Computer anxiety: relationship with computer experience and prevalence , 2001, Comput. Hum. Behav..

[41]  Roberta Di Pace,et al.  The impact of travel information's accuracy on route-choice , 2013 .

[42]  Pamela Murray-Tuite,et al.  Behavioral shifts after a fatal rapid transit accident: a multinomial logit model , 2014 .

[43]  Detlof von Winterfeldt,et al.  Exploring Reductions in London Underground Passenger Journeys Following the July 2005 Bombings , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[44]  Constantinos Antoniou,et al.  Development of a Mixed Multi-Nomial Logit Model to Capture the Impact of Information Systems on Travelers' Switching Behavior , 2007, J. Intell. Transp. Syst..

[45]  Glenn Lyons,et al.  Strategic review of travel information research , 2007 .

[46]  S. Chaiken,et al.  The psychology of attitudes. , 1993 .

[47]  Peter Bonsall,et al.  Traveller Behavior: Decision-Making in an Unpredictable World , 2004, J. Intell. Transp. Syst..

[48]  Tommy Gärling,et al.  DEVELOPMENT OF SCRIPT-BASED TRAVEL MODE CHOICE AFTER FORCED CHANGE , 2003 .

[49]  Glenn Lyons,et al.  The value of integrated multimodal traveller information and its potential contribution to modal change , 2003 .

[50]  S. Bamberg,et al.  Social context, personal norms and the use of public transportation: Two field studies , 2007 .

[51]  Wei Wang,et al.  Analyzing Travelers’ Intention to Accept Travel Information , 2010 .

[52]  Glenn Lyons,et al.  Explaining public transport information use when a car is available: attitude theory empirically investigated , 2010 .

[53]  J. Bortz,et al.  Forschungsmethoden und Evaluation , 1995 .

[54]  Ta Theo Arentze,et al.  Exploring the use of travel information - identifying contextual market segmentation in Seoul, Korea , 2011 .

[55]  Robert B. Cialdini,et al.  Descriptive Social Norms as Underappreciated Sources of Social Control , 2007 .