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Çevrimiçi Satın Almalarda Tüketicinin Risk Algısı: İki Boyutlu Ürün Görüntüleme ve Artırılmış Gerçeklik (Üç Boyutlu Ürün Görüntüleme) Uygulamalarına İlişkin Bir Karşılaştırma

Year 2018, Issue: 36, 53 - 76, 30.12.2018

Abstract

Her satın alma koşulunda olduğu gibi çevrimiçi satın almalarda da tüketici satın alma kararını verme aşamasında belirli seviyede risk ile karşı karşıya kalmaktadır. Çevrimiçi satın almalarda tüketicilerin ürün bilgisini toplama ve değerlendirme faaliyetleri algılanan riski ve dolayısıyla satın alma kararlarını doğrudan etkilemektedir. Günümüzde online perakendecilikle ilgili önemli gelişmelerden birisi ürün bilgisi toplama sırasında arttırılmış gerçeklik gibi yeni teknolojilerin kullanılmasıdır. Bu teknolojilerin sundukları faydalar arasında tüketicilerin bilgi toplama süreçlerini kolaylaştırmak ve satın alma öncesinde belli seviyede ürün deneme imkanını sunmak bulunmaktadır. Bu durum göz önüne alındığı zaman bu teknolojilerin tüketicilerin risk algısında da farklılıklar yaratması beklenmektedir. Bu çalışmanın temel amacı algılanan riskin boyutlarının farklı ürün görüntüleme teknolojileri bağlamında farklılıklarını tanımlamaktır. Tüketicilerin risk algısı arasındaki farklılıkların tanımlanabilmesi amacıyla tek faktörlü (2-boyutlu ve 3-boyutlu ürün görüntüleme) bir deney uygulanmıştır. Deneye İstanbul’da üniversite okumakta olan öğrenciler katılmıştır. Deneklerin tamamı ürün grubunun aksesuar olması nedeniyle kadınlardan oluşmaktadır. Riskin boyutlandırılması ve ürün görüntüleme koşulları arasındaki farklılıkların tanımlanabilmesi amacıyla Kısmi En Küçük Kareler yöntemi kullanılmıştır. Bulgular ürün görüntüleme teknolojilerinin tüketicilerin risk algısı üzerinde önemli farklılıklar yarattığını ortaya koymaktadır.

References

  • Akter, Shahriar, ve John D’ambra, Pradeep Ray (2011). “An evaluation of PLS based complex models: the roles of power analysis, predictive relevance and GoF index” [Bildiri]. Proceedinngs of the 17th Americas Conference on Information Systems (AMCIS2011). Detroit USA: Association for Information Systems: 1-7.
  • Algharabat, Raed, ve Ali Abdallah Alalwan, Niripendra P. Rana, Yogesh K. Dwivedi (2017). “Three dimensional product presentation quality antecedents and their consequences for online retailers: The moderating role of virtual product experience”. Journal of Retailing and Consumer Services, 36 (Mayıs): 203-217.
  • Algharabat, Raed S. (2014). “Conceptualising and modelling virtual product experience for online retailers”. International Journal of Internet Marketing and Advertising, 8(4): 300-319.
  • Azuma, Ronald T. (1997). “A survey of augmented reality”. Presence: Teleoperators and virtual environments, 6(4): 355-385.
  • Bagozzi, Richard P. (1994). Advanced methods of marketing research. USA: Blackwell Business.
  • Baytar, Fatma, ve Te-lin (Doreen) Chung, Eonyou S. (2016). “Can Augmented Can Augmented Reality Help E-shoppers Make Informed Purchases on Apparel Fit, Size, and Product Performance?”. International Textile and Apparel Association (ITAA) Annual Conference Proceedings. USA: Iowa State University: 95-96.
  • Baytar, Fatma, ve Susan Ashdown (2015). “An Exploratory Study of Interaction Patterns around the Use of Virtual Apparel Design and Try-on Technology”. Fashion Practice, 7(1): 31-52.
  • Beck, Marie, ve Dominique Crié. (2016). “I virtually try it… I want it! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions”. Journal of Retailing and Consumer Services, 40(Ocak):279- 286.
  • Bettman, James R. (1973). “Perceived risk and its components: a model and empirical test”. Journal of marketing research, 10(2): 184-190.
  • Bezes, Chistophe (2016). “Comparing online and in-store risks in multichannel shopping”. International Journal of Retail & Distribution Management, 44(3): 284- 300.
  • Biswas, Dipayan, ve Abhijit Biswas (2004). “The diagnostic role of signals in the context of perceived risks in online shopping: do signals matter more on the web?”. Journal of Interactive Marketing, 18(3): 30-45.
  • Chang, En-Chi, ve Ya-Fen Tseng (2013). “Research note: E-store image, perceived value and perceived risk”. Journal of Business Research, 66(7): 864-870.
  • Cunningham, Lawrence F., ve James H. Gerlach, Micheal D. Harper, Clifford E.Young, (2005). “Perceived risk and the consumer buying process: Internet airline reservations”. International Journal of Service Industry Management, 16(4): 357- 372.
  • Eggert, Axel (2006). “Intangibility and perceived risk in online environments”. Journal of Marketing Management, 22(5-6): 553-572.
  • Eurostat (2016). http://ec.europa.eu/eurostat/statistics-explained/index.php/Digital_ economy_and_society_statistics_-_households_and_individuals /Erişim Tarihi: 10.Haziran.2017.
  • Featherman, Mauricio, ve Mark Fuller (2003, Ocak). “Applying TAM to e-services adoption: the moderating role of perceived risk”. Proceedings of 36th Annual Hawaii International Conference on System Sciences. USA: IEEE: 1-11.
  • Featherman, Mauricio S., ve Paul A. Pavlou (2003). “Predicting e-services adoption: a perceived risk facets perspective”. International journal of human-computer studies, 59(4): 451-474.
  • Fiore, Ann Marie, ve Jihyun Kim, Hyun-Hwa Lee (2005). “Effect of image interactivity technology on consumer responses toward the online retailer”. Journal of Interactive Marketing, 19(3): 38-53.
  • Fornell, Claes, ve David F. Larcker (1981). “Evaluating structural equation models with unobservable variables and measurement error.” Journal of Marketing Research,18(1): 39-50.
  • Forsythe, Sandra,ve Chuanian Liu, David Shannon, Liu Chun Gardner (2006). “Development of a scale to measure the perceived benefits and risks of online shopping”. Journal of interactive marketing, 20(2): 55-75.
  • Girard, Tulay, ve Paul Dion (2010). “Validating the search, experience, and credence product classification framework”. Journal of Business Research, 63(9): 1079-1087.
  • Hair, Joe F., ve Christian M. Ringle, Marko Sarstedt (2011). “PLS-SEM: Indeed a silver bullet”. Journal of Marketing theory and Practice, 19(2): 139-152.
  • Hair, Joseph. F., ve G. Thomas M. Hult, Christian Ringle, Marko Sarstedt (2014). A primer on partial least squares structural equation modeling (PLS-SEM). USA: Sage Publications.
  • Howell, David C. (2010). Statistical methods for psychology. USA: Cengage Learning. Huang, Tseng-Lung, ve Hsu Liu Feng (2014). “Formation of augmented-reality interactive technology's persuasive effects from the perspective of experiential value”. Internet Research, 24(1): 82-109.
  • Javornik, Ana (2016). “Augmented Reality: Research Agenda for Studying The Impact of Its Media Characteristics on Consumer Behavior”. Journal of Retailing and Consumer Services, 30(Mayıs): 252-261.
  • Kang, Ju-Young M. (2014). “Augmented reality and motion capture apparel e-shopping values and usage intention”. International Journal of Clothing Science and Technology, 26(6): 486-499.
  • Kim, Jiyeon,ve Sandra Forsythe (2010). “Factors affecting adoption of product virtualization technology for çevrimiçi consumer electronics shopping”. International Journal of Retail & Distribution Management, 38(3): 190-204.
  • Laroche, Michel, ve Gordon H.G. McDougall, Jasmin Bergeron, Zhiyong Yang (2004). “Exploring how intangibility affects perceived risk”. Journal of Service Research, 6(4): 373-389.
  • Lee, Ming-Chi (2009). “Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit”. Electronic commerce research and applications, 8(3): 130-141.
  • Li, Hairong, ve Terry Daugherty, Frank Biocca (2003). “The role of virtual experience in consumer learning”. Journal of consumer psychology, 13(4): 395-407.
  • Zhao, Anita Lifen, ve Stuart Hanmer-Lloyd, Philippa Ward, Mark M.H. Goode (2008). “Perceived risk and Chinese consumers' internet banking services adoption”. International Journal of Bank Marketing, 26(7): 505-525.
  • Liljander, Veronica, ve Pia Polsa, Allard van Riel (2009). “Modelling consumer responses to an apparel store brand: Store image as a risk reducer”. Journal of Retailing and Consumer Services, 16(4): 281-290.
  • Lim, Nena (2003). “Consumers’ perceived risk: sources versus consequences”. Electronic Commerce Research and Applications, 2(3): 216-228.
  • Lopez-Nicolas, Carolina, ve Fransico Josè Molina-Castillo (2008). “Customer Knowledge Management and E-commerce: The role of customer perceived risk”. International Journal of Information Management, 28(2): 102-113.
  • Markopoulos, Panos M., ve Ravi Aron, Lyle H. Ungar (2016). “Product Information Websites: Are They Good for Consumers?”. Journal of Management Information Systems, 33(3): 624-651.
  • Merle, Aurèlie, Sylvain Senecal, Anik St-Onge (2012). “Whether and how virtual try-on influences consumer responses to an apparel web site”. International Journal of Electronic Commerce, 16(3): 41-64.
  • Mitchell, Vincent-Wayne (1999). “Consumer perceived risk: conceptualisations and models”. European Journal of marketing, 33(1/2): 163-195.
  • Miyazaki,Anthony D., ve Ana Fernandez (2001). “Consumer perceptions of privacy and security risks for online shopping”. Journal of Consumer affairs, 35(1): 27-44.
  • Nunnally, J. C.,& Bernstein, I.H. (1994). Psychometric theory. New York: McGraw-Hill.
  • Ozok, A.Ant, ve Anita Komlodi (2009). “Better in 3D? An empirical investigation of user satisfaction and preferences concerning two-dimensional and three-dimensional product representations in business-to-consumer e-commerce”. International Journal of Human–Computer Interaction, 25(4): 243-281.
  • Pachoulakis, Ioannis, ve Kostas Kapetanakis (2012). “Augmented reality platforms for virtual fitting rooms”. International Journal of Multimedia & Its Applications, 4(4): 35-46.
  • Pantano, Eleonora, ve Alexandra Rese, Daniel Baier (2017). “Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets”. Journal of Retailing and Consumer Services, 38(Eylül): 81-95.
  • Papagiannidis, Savvas, ve Eleonora Pantano, Eric W.K. See-To vd. (2017). To immerse or not? Experimenting with two virtual retail environments. Information Technology & People, 30(1): 163-188.
  • Pikkarainen, Tero, ve Kari Pikkarainen, Heikki Karjaluoto, Seppo Pahnila (2004). “Consumer acceptance of online banking: an extension of the technology acceptance model”. Internet research, 14(3): 224-235.
  • Pires, Guilherme, ve Dr. John Eckford (2004). “Influences on the perceived risk of purchasing online”. Journal of Consumer Behaviour, 4(2): 118-131.
  • Poushneh, Atieh, ve Arturo Z. Vasquez-Parraga (2017). “Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy”. Journal of Retailing and Consumer Services, 34(Ocak): 229-234.
  • Rese, Alexandra, ve Daniel BAier, Andreas Geyer-Schulz, Stepanie Schreiber (2016). “How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions”. Technological Forecasting and Social Change, 124(Kasım): 306-319.
  • Scholz, Joachim, ve Andrew N. Smith (2016). “Augmented reality: Designing immersive experiences that maximize consumer engagement”. Business Horizons, 59(2): 149- 161.
  • Shim, Soo In, ve Yuri Lee (2011). “Consumer's perceived risk reduction by 3D virtual model”. International Journal of Retail & Distribution Management, 39(12): 945- 959.
  • Shin, Dong Hee (2008). “Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities”. Interacting with computers, 20(4-5): 433-446.
  • Shin, Dong-Hee, ve Youn-Joo Shin (2011). “Consumers' trust in virtual mall shopping: The role of social presence and perceived security”. International Journal of Human-Computer Interaction, 27(5): 450-475.
  • Son, Jai-Yeoi, ve Sung S. Kim. (2008). “Internet users' information privacy-protective responses: A taxonomy and a nomological model”. MIS quarterly, 32(3): 503-529.
  • Spaid, Brain I., ve Daniel J. Flint (2014). “The meaning of shopping experiences augmented by mobile internet devices”. Journal of Marketing Theory and Practice, 22(1): 73-90.
  • Stone, Robert N., ve Kjell Grønhaug (1993). “Perceived risk: Further considerations for the marketing discipline”. European Journal of marketing, 27(3): 39-50.
  • Tenenhaus, Michel, ve Vincenzo Chatelin, Yves-Marie Lauro (2005). “PLS path modeling”. Computational statistics &data analysis, 48(1): 159-205.
  • Tenenhaus, Michel, ve Silvano Amato, Vincenzo Esposito Vinzi (2004, June). “A global goodness-of-fit index for PLS structural equation modelling”. Proceedings of the XLII SIS Scientific Meeting. Padova: CLEUP: 739-742.
  • Vinhal Nepomuceno, Marcelo, ve Michel Laroche, Marie-Odile Richard, Axel Eggert (2012). “Relationship between intangibility and perceived risk: moderating effect of privacy, system security and general security concerns”. Journal of Consumer Marketing, 29(3): 176-189.
  • Wodehouse, Andrew, ve Mohammed Abba (2016). “3D visualisation for online retail: factors in consumer behaviour”. International Journal of Market Research, 58(3): 6.
  • Yaoyuneyong, GAllayanne, ve Jamye K. Foster, Leisa R. Flynn (2014). “Factors impacting the efficacy of augmented reality virtual dressing room technology as a tool for online visual merchandising”. Journal of Global Fashion Marketing, 5(4): 283-296.
  • Yoo, Jungmin, ve Minjeong Kim (2014). “The effects of online product presentation on consumer responses: A mental imagery perspective”. Journal of Business Research, 67(11): 2464-2472.

Consumers’ Perceived Risk in Online Purchasing: A Comparison Concerning 2d Product Visualization and Augmented Reality Applications (3d Product Visualization)

Year 2018, Issue: 36, 53 - 76, 30.12.2018

Abstract

Consumers face a certain level of risk during online purchasing as any given purchase situation. During online purchases consumers’ information collection and processing activities directly affects their risk perception and thus purchasing decisions. One major development in online retailing today is the use of new technologies such as augmented reality during the collection of product information. The benefits offered by these technologies facilitate consumers' information gathering processes and offer a certain level of product testing prior to a purchase. When taken into consideration these technologies are expected to create differences in the risk perception of consumers. The main purpose of this study is to define the differences of perceived risk in the context of different product visualization technologies. A single-factor (2-D and 3-D product visualization) experiment was used to identify the differences between the risk perception of consumers. Students of a Istanbul University were used as subjects. As the product line used were accessories all of the subjects were female. To classify possible risk dimensions and to define the differences between two purchasing situations the data was analyzed with Partial Least Squares method. The findings suggest that product visualization technologies create a significant difference in consumers’ risk perception.

References

  • Akter, Shahriar, ve John D’ambra, Pradeep Ray (2011). “An evaluation of PLS based complex models: the roles of power analysis, predictive relevance and GoF index” [Bildiri]. Proceedinngs of the 17th Americas Conference on Information Systems (AMCIS2011). Detroit USA: Association for Information Systems: 1-7.
  • Algharabat, Raed, ve Ali Abdallah Alalwan, Niripendra P. Rana, Yogesh K. Dwivedi (2017). “Three dimensional product presentation quality antecedents and their consequences for online retailers: The moderating role of virtual product experience”. Journal of Retailing and Consumer Services, 36 (Mayıs): 203-217.
  • Algharabat, Raed S. (2014). “Conceptualising and modelling virtual product experience for online retailers”. International Journal of Internet Marketing and Advertising, 8(4): 300-319.
  • Azuma, Ronald T. (1997). “A survey of augmented reality”. Presence: Teleoperators and virtual environments, 6(4): 355-385.
  • Bagozzi, Richard P. (1994). Advanced methods of marketing research. USA: Blackwell Business.
  • Baytar, Fatma, ve Te-lin (Doreen) Chung, Eonyou S. (2016). “Can Augmented Can Augmented Reality Help E-shoppers Make Informed Purchases on Apparel Fit, Size, and Product Performance?”. International Textile and Apparel Association (ITAA) Annual Conference Proceedings. USA: Iowa State University: 95-96.
  • Baytar, Fatma, ve Susan Ashdown (2015). “An Exploratory Study of Interaction Patterns around the Use of Virtual Apparel Design and Try-on Technology”. Fashion Practice, 7(1): 31-52.
  • Beck, Marie, ve Dominique Crié. (2016). “I virtually try it… I want it! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions”. Journal of Retailing and Consumer Services, 40(Ocak):279- 286.
  • Bettman, James R. (1973). “Perceived risk and its components: a model and empirical test”. Journal of marketing research, 10(2): 184-190.
  • Bezes, Chistophe (2016). “Comparing online and in-store risks in multichannel shopping”. International Journal of Retail & Distribution Management, 44(3): 284- 300.
  • Biswas, Dipayan, ve Abhijit Biswas (2004). “The diagnostic role of signals in the context of perceived risks in online shopping: do signals matter more on the web?”. Journal of Interactive Marketing, 18(3): 30-45.
  • Chang, En-Chi, ve Ya-Fen Tseng (2013). “Research note: E-store image, perceived value and perceived risk”. Journal of Business Research, 66(7): 864-870.
  • Cunningham, Lawrence F., ve James H. Gerlach, Micheal D. Harper, Clifford E.Young, (2005). “Perceived risk and the consumer buying process: Internet airline reservations”. International Journal of Service Industry Management, 16(4): 357- 372.
  • Eggert, Axel (2006). “Intangibility and perceived risk in online environments”. Journal of Marketing Management, 22(5-6): 553-572.
  • Eurostat (2016). http://ec.europa.eu/eurostat/statistics-explained/index.php/Digital_ economy_and_society_statistics_-_households_and_individuals /Erişim Tarihi: 10.Haziran.2017.
  • Featherman, Mauricio, ve Mark Fuller (2003, Ocak). “Applying TAM to e-services adoption: the moderating role of perceived risk”. Proceedings of 36th Annual Hawaii International Conference on System Sciences. USA: IEEE: 1-11.
  • Featherman, Mauricio S., ve Paul A. Pavlou (2003). “Predicting e-services adoption: a perceived risk facets perspective”. International journal of human-computer studies, 59(4): 451-474.
  • Fiore, Ann Marie, ve Jihyun Kim, Hyun-Hwa Lee (2005). “Effect of image interactivity technology on consumer responses toward the online retailer”. Journal of Interactive Marketing, 19(3): 38-53.
  • Fornell, Claes, ve David F. Larcker (1981). “Evaluating structural equation models with unobservable variables and measurement error.” Journal of Marketing Research,18(1): 39-50.
  • Forsythe, Sandra,ve Chuanian Liu, David Shannon, Liu Chun Gardner (2006). “Development of a scale to measure the perceived benefits and risks of online shopping”. Journal of interactive marketing, 20(2): 55-75.
  • Girard, Tulay, ve Paul Dion (2010). “Validating the search, experience, and credence product classification framework”. Journal of Business Research, 63(9): 1079-1087.
  • Hair, Joe F., ve Christian M. Ringle, Marko Sarstedt (2011). “PLS-SEM: Indeed a silver bullet”. Journal of Marketing theory and Practice, 19(2): 139-152.
  • Hair, Joseph. F., ve G. Thomas M. Hult, Christian Ringle, Marko Sarstedt (2014). A primer on partial least squares structural equation modeling (PLS-SEM). USA: Sage Publications.
  • Howell, David C. (2010). Statistical methods for psychology. USA: Cengage Learning. Huang, Tseng-Lung, ve Hsu Liu Feng (2014). “Formation of augmented-reality interactive technology's persuasive effects from the perspective of experiential value”. Internet Research, 24(1): 82-109.
  • Javornik, Ana (2016). “Augmented Reality: Research Agenda for Studying The Impact of Its Media Characteristics on Consumer Behavior”. Journal of Retailing and Consumer Services, 30(Mayıs): 252-261.
  • Kang, Ju-Young M. (2014). “Augmented reality and motion capture apparel e-shopping values and usage intention”. International Journal of Clothing Science and Technology, 26(6): 486-499.
  • Kim, Jiyeon,ve Sandra Forsythe (2010). “Factors affecting adoption of product virtualization technology for çevrimiçi consumer electronics shopping”. International Journal of Retail & Distribution Management, 38(3): 190-204.
  • Laroche, Michel, ve Gordon H.G. McDougall, Jasmin Bergeron, Zhiyong Yang (2004). “Exploring how intangibility affects perceived risk”. Journal of Service Research, 6(4): 373-389.
  • Lee, Ming-Chi (2009). “Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit”. Electronic commerce research and applications, 8(3): 130-141.
  • Li, Hairong, ve Terry Daugherty, Frank Biocca (2003). “The role of virtual experience in consumer learning”. Journal of consumer psychology, 13(4): 395-407.
  • Zhao, Anita Lifen, ve Stuart Hanmer-Lloyd, Philippa Ward, Mark M.H. Goode (2008). “Perceived risk and Chinese consumers' internet banking services adoption”. International Journal of Bank Marketing, 26(7): 505-525.
  • Liljander, Veronica, ve Pia Polsa, Allard van Riel (2009). “Modelling consumer responses to an apparel store brand: Store image as a risk reducer”. Journal of Retailing and Consumer Services, 16(4): 281-290.
  • Lim, Nena (2003). “Consumers’ perceived risk: sources versus consequences”. Electronic Commerce Research and Applications, 2(3): 216-228.
  • Lopez-Nicolas, Carolina, ve Fransico Josè Molina-Castillo (2008). “Customer Knowledge Management and E-commerce: The role of customer perceived risk”. International Journal of Information Management, 28(2): 102-113.
  • Markopoulos, Panos M., ve Ravi Aron, Lyle H. Ungar (2016). “Product Information Websites: Are They Good for Consumers?”. Journal of Management Information Systems, 33(3): 624-651.
  • Merle, Aurèlie, Sylvain Senecal, Anik St-Onge (2012). “Whether and how virtual try-on influences consumer responses to an apparel web site”. International Journal of Electronic Commerce, 16(3): 41-64.
  • Mitchell, Vincent-Wayne (1999). “Consumer perceived risk: conceptualisations and models”. European Journal of marketing, 33(1/2): 163-195.
  • Miyazaki,Anthony D., ve Ana Fernandez (2001). “Consumer perceptions of privacy and security risks for online shopping”. Journal of Consumer affairs, 35(1): 27-44.
  • Nunnally, J. C.,& Bernstein, I.H. (1994). Psychometric theory. New York: McGraw-Hill.
  • Ozok, A.Ant, ve Anita Komlodi (2009). “Better in 3D? An empirical investigation of user satisfaction and preferences concerning two-dimensional and three-dimensional product representations in business-to-consumer e-commerce”. International Journal of Human–Computer Interaction, 25(4): 243-281.
  • Pachoulakis, Ioannis, ve Kostas Kapetanakis (2012). “Augmented reality platforms for virtual fitting rooms”. International Journal of Multimedia & Its Applications, 4(4): 35-46.
  • Pantano, Eleonora, ve Alexandra Rese, Daniel Baier (2017). “Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets”. Journal of Retailing and Consumer Services, 38(Eylül): 81-95.
  • Papagiannidis, Savvas, ve Eleonora Pantano, Eric W.K. See-To vd. (2017). To immerse or not? Experimenting with two virtual retail environments. Information Technology & People, 30(1): 163-188.
  • Pikkarainen, Tero, ve Kari Pikkarainen, Heikki Karjaluoto, Seppo Pahnila (2004). “Consumer acceptance of online banking: an extension of the technology acceptance model”. Internet research, 14(3): 224-235.
  • Pires, Guilherme, ve Dr. John Eckford (2004). “Influences on the perceived risk of purchasing online”. Journal of Consumer Behaviour, 4(2): 118-131.
  • Poushneh, Atieh, ve Arturo Z. Vasquez-Parraga (2017). “Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy”. Journal of Retailing and Consumer Services, 34(Ocak): 229-234.
  • Rese, Alexandra, ve Daniel BAier, Andreas Geyer-Schulz, Stepanie Schreiber (2016). “How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions”. Technological Forecasting and Social Change, 124(Kasım): 306-319.
  • Scholz, Joachim, ve Andrew N. Smith (2016). “Augmented reality: Designing immersive experiences that maximize consumer engagement”. Business Horizons, 59(2): 149- 161.
  • Shim, Soo In, ve Yuri Lee (2011). “Consumer's perceived risk reduction by 3D virtual model”. International Journal of Retail & Distribution Management, 39(12): 945- 959.
  • Shin, Dong Hee (2008). “Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities”. Interacting with computers, 20(4-5): 433-446.
  • Shin, Dong-Hee, ve Youn-Joo Shin (2011). “Consumers' trust in virtual mall shopping: The role of social presence and perceived security”. International Journal of Human-Computer Interaction, 27(5): 450-475.
  • Son, Jai-Yeoi, ve Sung S. Kim. (2008). “Internet users' information privacy-protective responses: A taxonomy and a nomological model”. MIS quarterly, 32(3): 503-529.
  • Spaid, Brain I., ve Daniel J. Flint (2014). “The meaning of shopping experiences augmented by mobile internet devices”. Journal of Marketing Theory and Practice, 22(1): 73-90.
  • Stone, Robert N., ve Kjell Grønhaug (1993). “Perceived risk: Further considerations for the marketing discipline”. European Journal of marketing, 27(3): 39-50.
  • Tenenhaus, Michel, ve Vincenzo Chatelin, Yves-Marie Lauro (2005). “PLS path modeling”. Computational statistics &data analysis, 48(1): 159-205.
  • Tenenhaus, Michel, ve Silvano Amato, Vincenzo Esposito Vinzi (2004, June). “A global goodness-of-fit index for PLS structural equation modelling”. Proceedings of the XLII SIS Scientific Meeting. Padova: CLEUP: 739-742.
  • Vinhal Nepomuceno, Marcelo, ve Michel Laroche, Marie-Odile Richard, Axel Eggert (2012). “Relationship between intangibility and perceived risk: moderating effect of privacy, system security and general security concerns”. Journal of Consumer Marketing, 29(3): 176-189.
  • Wodehouse, Andrew, ve Mohammed Abba (2016). “3D visualisation for online retail: factors in consumer behaviour”. International Journal of Market Research, 58(3): 6.
  • Yaoyuneyong, GAllayanne, ve Jamye K. Foster, Leisa R. Flynn (2014). “Factors impacting the efficacy of augmented reality virtual dressing room technology as a tool for online visual merchandising”. Journal of Global Fashion Marketing, 5(4): 283-296.
  • Yoo, Jungmin, ve Minjeong Kim (2014). “The effects of online product presentation on consumer responses: A mental imagery perspective”. Journal of Business Research, 67(11): 2464-2472.
There are 60 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Tuğçe Ozansoy Çadırcı

Ayşegül Sağkaya Güngör

Publication Date December 30, 2018
Published in Issue Year 2018 Issue: 36

Cite

APA Ozansoy Çadırcı, T., & Sağkaya Güngör, A. (2018). Çevrimiçi Satın Almalarda Tüketicinin Risk Algısı: İki Boyutlu Ürün Görüntüleme ve Artırılmış Gerçeklik (Üç Boyutlu Ürün Görüntüleme) Uygulamalarına İlişkin Bir Karşılaştırma. Kocaeli Üniversitesi Sosyal Bilimler Dergisi(36), 53-76.

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