{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/22007"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/22007","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Incorporating consumer resistance to innovation in a new product diffusion model: A new model and a simulation comparison with existing models","abstract":"This dissertation proposes a new diffusion model for an innovation in durable goods markets and compares the model with four existing models. The distinctive feature of the new diffusion model is an explicit consideration of the competition between an existing product and a new product due to the comparative advantage of the new product and also due to the closer introduction times of the existing product and the new product. Adopting an individual-level modeling approaching, this diffusion model incorporates the phenomena of: interaction of evaluations for successive generation innovations, risk-adjusted utility of the new product, increased new product utility over time, and the Bayesian process of uncertainty reduction. The proposed model has been compared with existing models using both empirical data from the color TV market, and computer-simulated market data. The comparison criteria are (1) goodness of fit in model estimation samples, and (2) forecast accuracy in model validation samples. The results of empirical comparison show that the proposed model performs better than the compared models on both criteria. The results of computer simulation comparison show that the proposed model and Lattin and Roberts' (1989) RAU model are the two best models with the latter being better than the former on goodness-of-fit in seven of twenty-eight market types, and the former being better than the latter on the accuracy of one-step-ahead sales forecasting in twenty-six markets. In addition, in markets characterized by strong consumer resistance, the proposed model is superior to the RAU model on both performance criteria. The proposed model is also superior to the Bass model (1969), a first-order-autoregressive model, and the Lattin and Roberts' (1989) model with price consideration in all the markets examined. Besides, the superiority of the proposed model to these three models increases more often in markets in which diffusion-deterring factors are present. Therefore, the proposed model has demonstrated its superior capabilities in modeling the diffusion of a new product in an environment characterized by stronger consumer resistance. Managerial implications of the proposed model in new product prelaunch forecasting and post-introduction adoption diagnosis are also discussed.","abstract_html":"This dissertation proposes a new diffusion model for an innovation in durable goods markets and compares the model with four existing models. The distinctive feature of the new diffusion model is an explicit consideration of the competition between an existing product and a new product due to the comparative advantage of the new product and also due to the closer introduction times of the existing product and the new product. Adopting an individual-level modeling approaching, this diffusion model incorporates the phenomena of: interaction of evaluations for successive generation innovations, risk-adjusted utility of the new product, increased new product utility over time, and the Bayesian process of uncertainty reduction. The proposed model has been compared with existing models using both empirical data from the color TV market, and computer-simulated market data. The comparison criteria are (1) goodness of fit in model estimation samples, and (2) forecast accuracy in model validation samples. The results of empirical comparison show that the proposed model performs better than the compared models on both criteria. The results of computer simulation comparison show that the proposed model and Lattin and Roberts' (1989) RAU model are the two best models with the latter being better than the former on goodness-of-fit in seven of twenty-eight market types, and the former being better than the latter on the accuracy of one-step-ahead sales forecasting in twenty-six markets. In addition, in markets characterized by strong consumer resistance, the proposed model is superior to the RAU model on both performance criteria. The proposed model is also superior to the Bass model (1969), a first-order-autoregressive model, and the Lattin and Roberts' (1989) model with price consideration in all the markets examined. Besides, the superiority of the proposed model to these three models increases more often in markets in which diffusion-deterring factors are present. Therefore, the proposed model has demonstrated its superior capabilities in modeling the diffusion of a new product in an environment characterized by stronger consumer resistance. Managerial implications of the proposed model in new product prelaunch forecasting and post-introduction adoption diagnosis are also discussed.","abstract_has_math":false,"creators":["Chang, Ai-Hwa"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Business Administration","degree_department":null,"school":null,"contributors":["Sudharshan, Devanathan"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1992,"date_issued":"1992","date_published":"1992","updated_at":"2026-07-22T22:25:19Z","subjects":["Business Administration, Marketing"],"languages":["eng"],"rights":["Copyright 1992 Chang, Ai-Hwa"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9236415","(UMI)AAI9236415"],"render_values":[{"text":"AAI9236415","href":null,"code":true},{"text":"(UMI)AAI9236415","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/22007","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sudharshan, Devanathan"]},{"key":"dc:creator","label":"Author","values":["Chang, Ai-Hwa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["1992","2011-05-07T13:25:58Z","10000-01-01"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Business Administration"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Business Administration, Marketing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1992 Chang, Ai-Hwa"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9236415","(UMI)AAI9236415","http://hdl.handle.net/2142/22007"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation proposes a new diffusion model for an innovation in durable goods markets and compares the model with four existing models. The distinctive feature of the new diffusion model is an explicit consideration of the competition between an existing product and a new product due to the comparative advantage of the new product and also due to the closer introduction times of the existing product and the new product. Adopting an individual-level modeling approaching, this diffusion model incorporates the phenomena of: interaction of evaluations for successive generation innovations, risk-adjusted utility of the new product, increased new product utility over time, and the Bayesian process of uncertainty reduction. The proposed model has been compared with existing models using both empirical data from the color TV market, and computer-simulated market data. The comparison criteria are (1) goodness of fit in model estimation samples, and (2) forecast accuracy in model validation samples. The results of empirical comparison show that the proposed model performs better than the compared models on both criteria. The results of computer simulation comparison show that the proposed model and Lattin and Roberts' (1989) RAU model are the two best models with the latter being better than the former on goodness-of-fit in seven of twenty-eight market types, and the former being better than the latter on the accuracy of one-step-ahead sales forecasting in twenty-six markets. In addition, in markets characterized by strong consumer resistance, the proposed model is superior to the RAU model on both performance criteria. The proposed model is also superior to the Bass model (1969), a first-order-autoregressive model, and the Lattin and Roberts' (1989) model with price consideration in all the markets examined. Besides, the superiority of the proposed model to these three models increases more often in markets in which diffusion-deterring factors are present. Therefore, the proposed model has demonstrated its superior capabilities in modeling the diffusion of a new product in an environment characterized by stronger consumer resistance. Managerial implications of the proposed model in new product prelaunch forecasting and post-introduction adoption diagnosis are also discussed.","Made available in DSpace on 2011-05-07T13:25:58Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9236415.pdf: 10052735 bytes, checksum: 67c36b8d2dc8b496fab527c9f765bce1 (MD5) Previous issue date: 1992","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:54:41Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:25:26-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Incorporating consumer resistance to innovation in a new product diffusion model: A new model and a simulation comparison with existing models"]}]}],"canonical_facts":{"dc:contributor":["Sudharshan, Devanathan"],"dc:creator":["Chang, Ai-Hwa"],"dc:date":["1992","2011-05-07T13:25:58Z","10000-01-01"],"dc:description":["This dissertation proposes a new diffusion model for an innovation in durable goods markets and compares the model with four existing models. The distinctive feature of the new diffusion model is an explicit consideration of the competition between an existing product and a new product due to the comparative advantage of the new product and also due to the closer introduction times of the existing product and the new product. Adopting an individual-level modeling approaching, this diffusion model incorporates the phenomena of: interaction of evaluations for successive generation innovations, risk-adjusted utility of the new product, increased new product utility over time, and the Bayesian process of uncertainty reduction. The proposed model has been compared with existing models using both empirical data from the color TV market, and computer-simulated market data. The comparison criteria are (1) goodness of fit in model estimation samples, and (2) forecast accuracy in model validation samples. The results of empirical comparison show that the proposed model performs better than the compared models on both criteria. The results of computer simulation comparison show that the proposed model and Lattin and Roberts' (1989) RAU model are the two best models with the latter being better than the former on goodness-of-fit in seven of twenty-eight market types, and the former being better than the latter on the accuracy of one-step-ahead sales forecasting in twenty-six markets. In addition, in markets characterized by strong consumer resistance, the proposed model is superior to the RAU model on both performance criteria. The proposed model is also superior to the Bass model (1969), a first-order-autoregressive model, and the Lattin and Roberts' (1989) model with price consideration in all the markets examined. Besides, the superiority of the proposed model to these three models increases more often in markets in which diffusion-deterring factors are present. Therefore, the proposed model has demonstrated its superior capabilities in modeling the diffusion of a new product in an environment characterized by stronger consumer resistance. Managerial implications of the proposed model in new product prelaunch forecasting and post-introduction adoption diagnosis are also discussed.","Made available in DSpace on 2011-05-07T13:25:58Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9236415.pdf: 10052735 bytes, checksum: 67c36b8d2dc8b496fab527c9f765bce1 (MD5) Previous issue date: 1992","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:54:41Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:25:26-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"],"dc:identifier":["AAI9236415","(UMI)AAI9236415","http://hdl.handle.net/2142/22007"],"dc:language":["eng"],"dc:rights":["Copyright 1992 Chang, Ai-Hwa"],"dc:subject":["Business Administration, Marketing"],"dc:title":["Incorporating consumer resistance to innovation in a new product diffusion model: A new model and a simulation comparison with existing models"],"dc:type":["text"],"thesis:degree_discipline":["Business Administration"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:19Z"}