Domestic Technology Adoption: Comparison of Innovation Adoption Models and Moderators

Domestic technologies, such as assistant robots, have the potential to provide considerable assistance to families in societies with aging populations and increasing labor costs. This study intends 1 to test a series of innovation adoption theories to examine which models may better predict consumer behavioral intention toward the use of domestic technologies and 2 to examine whether lead-usership and global identity predict intentions. With the floor cleaning robots as target products of the survey and employing a sample of 299 potential consumers in Taiwan, a rapidly aging society, this study finds: 1 the theory of planned behavior TPB model accounts for 55% of the variance and better predicts purchase intention than the technology acceptance model and the theory of reasoned action. 2 In the nested TPB model, the effects of usefulness and ease of use on intentions are fully mediated by attitude. 3 When including 2 additional constructs, global identity and lead-usership, the explanatory power of the extended TPB model rises from 55% to 66%. 4 Lead-usership moderates the link between attitude and intentions, that is, the stronger the lead-usership the weaker the effect of attitude on intentions. 5 As lead-usership and global identity are included in the model, the impact of perceived behavioral control vanishes. 6 Subjective norms moderate weakening the effect of attitude on adoption intentions; thus, word of mouth and peer pressure could be powerful communication tools to persuade follower consumers to adopt domestic technologies, such as family robots.

[1]  Gaby Odekerken-Schröder,et al.  Using PLS path modeling for assessing hierarchial construct models: guidelines and impirical illustration , 2009 .

[2]  Eric Becker,et al.  Digital cities of the future: Extending @home assistive technologies for the elderly and the disabled , 2011, Telematics Informatics.

[3]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[4]  Chung-Chi Shen,et al.  Marketing communication strategies in support of product launch: An empirical study of Taiwanese high-tech firms , 2007 .

[5]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[6]  Chorng-Shyong Ong,et al.  Gender differences in perceptions and relationships among dominants of e-learning acceptance , 2006, Comput. Hum. Behav..

[7]  G. Tellis,et al.  Research on Innovation: A Review and Agenda for Marketing Science , 2006 .

[8]  Paul L. Sauer,et al.  Using Moderator Variables in Structural Equation Models , 1993 .

[9]  Yikuan Lee,et al.  New product launch strategy for network effects products , 2003 .

[10]  David J. Faulds,et al.  Social media: The new hybrid element of the promotion mix , 2009 .

[11]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[12]  D. Straub,et al.  Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly , 2012 .

[13]  Shirley Taylor,et al.  Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions , 1995 .

[14]  V. Venkatesh,et al.  AGE DIFFERENCES IN TECHNOLOGY ADOPTION DECISIONS: IMPLICATIONS FOR A CHANGING WORK FORCE , 2000 .

[15]  Michel Laroche,et al.  Identity, demographics, and consumer behaviors , 2011 .

[16]  Paul A. Pavlou,et al.  From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The Case of New Product Development , 2006, Inf. Syst. Res..

[17]  C. Shapiro,et al.  Technology Adoption in the Presence of Network Externalities , 1986, Journal of Political Economy.

[18]  G. Marchi,et al.  Extending lead-user theory to online brand communities: The case of the community Ducati , 2011 .

[19]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[20]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[21]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[22]  F. Bookstein,et al.  Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory: , 1982 .

[23]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[24]  Blair H. Sheppard,et al.  The Theory of Reasoned Action: A Meta-Analysis of Past Research with Recommendations for Modifications and Future Research , 1988 .

[25]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[26]  Ehud Sharlin,et al.  Toward Acceptable Domestic Robots: Applying Insights from Social Psychology , 2009, Int. J. Soc. Robotics.

[27]  A. Der-Karabetian,et al.  Affective Bicultural and Global-Human Identity Scales for Mexican-American Adolescents , 1997, Psychological reports.

[28]  Alexander Serenko,et al.  User acceptance of hedonic digital artifacts: A theory of consumption values perspective , 2010, Inf. Manag..

[29]  Per E. Pedersen,et al.  Explaining intention to use mobile chat services: moderating effects of gender , 2005 .

[30]  Hokyoung Ryu,et al.  Learner Acceptance of a Multimedia-Based Learning System , 2013, Int. J. Hum. Comput. Interact..

[31]  David C. Yen,et al.  Exploring the Individual's Behavior on Self-Disclosure Online , 2012, Int. J. Hum. Comput. Interact..

[32]  I. Ajzen The theory of planned behavior , 1991 .

[33]  Wan-I Lee,et al.  Assessing the effects of consumer involvement and service quality in a self‐service setting , 2011 .

[34]  E. Deci,et al.  The "What" and "Why" of Goal Pursuits: Human Needs and the Self-Determination of Behavior , 2000 .

[35]  Hyewon Chung,et al.  Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS , 2013, Int. J. Hum. Comput. Interact..

[36]  E. Hippel,et al.  Lead users: a source of novel product concepts , 1986 .

[37]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[38]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[39]  John Roberts,et al.  The nature of lead users and measurement of leading edge status , 2004 .

[40]  Muammer Ozer The roles of product lead-users and product experts in new product evaluation , 2009 .

[41]  D. DavisFred,et al.  User Acceptance of Computer Technology , 1989 .

[42]  Mark E. Parry,et al.  Incorporating network externalities into the technology acceptance model , 2009 .

[43]  Mary Jo Bitner,et al.  Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies , 2005 .

[44]  J. Scott Armstrong,et al.  Estimating nonresponse bias in mail surveys. , 1977 .

[45]  Jan Wieseke,et al.  Social influence on salespeople’s adoption of sales technology: a multilevel analysis , 2010 .

[46]  Timothy Teo,et al.  Understanding the Intention to Use Technology by Preservice Teachers: An Empirical Test of Competing Theoretical Models , 2012, Int. J. Hum. Comput. Interact..

[47]  Peter R. Magnusson,et al.  Technology readiness and usage: a global-identity perspective , 2009 .

[48]  Martin Wetzels,et al.  A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects , 2007, Inf. Manag..

[49]  Marco Ceccarelli,et al.  Service Robots and Robotics: Design and Application , 2012 .

[50]  Roger J. Calantone,et al.  A comparison of three models to explain shop‐bot use on the web , 2002 .

[51]  Michel Tenenhaus,et al.  PLS path modeling , 2005, Comput. Stat. Data Anal..

[52]  Margherita Pagani Determinants of adoption of third generation mobile multimedia services , 2004 .

[53]  Marko Sarstedt,et al.  An assessment of the use of partial least squares structural equation modeling in marketing research , 2012 .

[54]  Ferdinando Fornara,et al.  Robots in a domestic setting: a psychological approach , 2005, Universal Access in the Information Society.

[55]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[56]  Nikos Bozionelos,et al.  Socio-economic background and computer use: the role of computer anxiety and computer experience in their relationship , 2004, Int. J. Hum. Comput. Stud..

[57]  Kelly Weidner,et al.  Enhancing New Product Adoption at the Base of the Pyramid: A Contextualized Model , 2012 .

[58]  J. Steenkamp,et al.  Consumer attitudes toward marketplace globalization: Structure, antecedents and consequences , 2006 .

[59]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[60]  Herbjørn Nysveen,et al.  This is who I am ” : Identity Expressiveness and the Theory of Planned Behavior Forthcoming in Psychology & Marketing , 2015 .

[61]  I. Ajzen,et al.  Prediction of goal directed behaviour: Attitudes, intentions and perceived behavioural control , 1986 .

[62]  J. W. Taylor The role of risk in consumer behavior. , 1974 .

[63]  Frank Q. Fu,et al.  Motivating Salespeople to Sell New Products: the Relative Influence of Attitudes, Subjective Norms, and Self-efficacy Literature Review: New Product Performance, Tpb, and the Sales Force Intentions and Sales Performance the Relative Influence of Attitudes, Subjective Norms, and Self-efficacy the Mod , 2022 .

[64]  Dong Hee Shin,et al.  User acceptance of mobile Internet: Implication for convergence technologies , 2007, Interact. Comput..

[65]  I. Ajzen The theory of planned behaviour: Reactions and reflections , 2011, Psychology & health.

[66]  Bill Gates,et al.  A robot in every home. , 2007 .