The dynamics of technological substitution: the case of eco-innovation diffusion of surface cleaning products

Some eco-innovations have already reached a mature state, but they diffuse slowly. There is little known about the importance of various factors on the diffusion process of eco-innovations. The aim of this research is to propose a conceptual model for eco-innovation diffusion, where particular case study of eco-innovation – micro-fibre cloth (MFC) for surface cleaning purposes – is given. The work will study the relative importance of various motivations on diffusion processes as well as the influence of information campaigns. This novel methodology has been developed under the system dynamics framework and is coupled with the logistic regression model. Structural validation tests were done for the proposed model. The methodology is proposed, then the integrated empirical study and system dynamics model are completed. The results of the logistic regression models show that the overall attitudes and social influence has the most dominant impact on intention to use the studied eco-innovation products. The most sensitive parameters in the system dynamics model were found to be the adoption faction of information received by word-of-mouth, households adopting micro fibre cloth at the beginning of the simulation, and the contact rate per household. The proposed methodology, and developed mathematical model can also be used as the basis for other studies of other diffusion processes, since system dynamics modelling is a white-box modelling approach, and the structure of the model can be enhanced with the latest results from other studies.

[1]  T. Magnusson,et al.  Strategic niche management from a business perspective : taking cleaner vehicle technologies from prototype to series production , 2014 .

[2]  Paul S Phillips,et al.  Determining the drivers for householder pro-environmental behaviour: waste minimisation compared to recycling , 2004 .

[3]  Thomas Schneider,et al.  Micro-fibre and ultra-micro-fibre cloths, their physical characteristics, cleaning effect, abrasion on surfaces, friction, and wear resistance , 2002 .

[4]  M. Porter.  Competitive Advantage: Creating and Sustaining Superior Performance , 1985 .

[5]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[6]  Mao-Shong Lin,et al.  Identifying the determinants of broadband adoption by diffusion stage in OECD countries , 2013 .

[7]  M. Cortimiglia,et al.  Success factors for environmentally sustainable product innovation: a systematic literature review , 2014 .

[8]  S. Bamberg.  How does environmental concern influence specific environmentally related behaviors? A new answer to an old question , 2003 .

[9]  C. Ghisetti,et al.  Environmental innovations and profitability: How does it pay to be green? An empirical analysis on the German innovation survey , 2014 .

[10]  K. Rennings.  Redefining innovation -- eco-innovation research and the contribution from ecological economics , 2000 .

[11]  Jürgen Weigand,et al.  Agent-based simulation of policy induced diffusion of smart meters , 2014 .

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

[13]  L. Steg,et al.  An Integrated Framework for Encouraging Pro-environmental Behaviour: The role of values, situational factors and goals , 2014 .

[14]  L. Steg,et al.  Normative, Gain and Hedonic Goal Frames Guiding Environmental Behavior , 2007 .

[15]  Ali Diabat,et al.  Analyzing the drivers of green manufacturing with fuzzy approach , 2015 .

[16]  J. Holah,et al.  Assessing the efficacy of different microfibre cloths at removing surface micro-organisms associated with healthcare-associated infections. , 2011, The Journal of hospital infection.

[17]  V. Gant,et al.  Removing bacteria from hospital surfaces: a laboratory comparison of ultramicrofibre and standard cloths. , 2008, The Journal of hospital infection.

[18]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[19]  F. Bass.  A new product growth model for consumer durables , 1976 .

[20]  Martin Wietschel,et al.  Modelling market diffusion of electric vehicles with real world driving data — Part I: Model structure and validation , 2014 .

[21]  V. Mahajan,et al.  Innovation diffusion and new product growth models: A critical review and research directions , 2010 .

[22]  K. Frenken,et al.  Thresholds models of technological transitions , 2014 .

[23]  J. Forrester.  Industrial Dynamics: A Major Breakthrough for Decision Makers , 2012 .

[24]  P. Stern.  New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior , 2000 .

[25]  S. Rout,et al.  Evaluation of the cleaning efficiency of microfibre cloths processed via an ozonated laundry system , 2012 .

[26]  N. Meade,et al.  Modelling and forecasting the diffusion of innovation – A 25-year review , 2006 .

[27]  Troy D. Abel,et al.  A Value-Belief-Norm Theory of Support for Social Movements: The Case of Environmentalism , 1999 .

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

[29]  Antonio Hidalgo,et al.  Diffusion of eco-innovations: A review , 2014 .

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

[31]  R. Ozaki.  Adopting sustainable innovation: what makes consumers sign up to green electricity? , 2011 .

[32]  I. Hertz-Picciotto,et al.  Passive sampling methods to determine household and personal care product use , 2012, Journal of Exposure Science and Environmental Epidemiology.

[33]  John D. Sterman,et al.  System Dynamics: Systems Thinking and Modeling for a Complex World , 2002 .

[34]  Nina Schwarz,et al.  Agent-based modeling of the diffusion of environmental innovations — An empirical approach , 2009 .

[35]  Yaman Barlas,et al.  Formal aspects of model validity and validation in system dynamics , 1996 .

[36]  C. Vlek,et al.  A review of intervention studies aimed at household energy conservation , 2005 .