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Enregistrement W4226072184 · doi:10.21271/zjhs.25.6.15

The impact of buyer shopping orientations and demographic factors on the purchasing for different product types- in the context of online shopping

2021· article· en· W4226072184 sur OpenAlexaboutno aff
Haseba Hamad

Notice bibliographique

RevueZanco Journal of Humanity Sciences · 2021
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueTechnology Adoption and User Behaviour
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPurchasingContext (archaeology)Product (mathematics)AdvertisingBusinessMarketingPsychologyMathematicsGeography

Résumé

récupéré en direct d'OpenAlex

This study examines the impact of buyer shopping orientations and demographic factors on the purchasing for different product categories in the context of online shopping. To validate the study conceptual framework this research employs quantitative -method research in order to achieve the highest possible validity and reliability of the results. The quantitative data presented in this study were collected from an e-survey of consumers in the Kurdistan region/ Iraq using a self-administered questionnaire. This method was chosen, due to the fact that it is time and cost efficient compared to other distribution methods (Aaker et al. 2006). The sample consisted of 300 responses and was collected among consumers in the Kurdistan region/ Iraq. Structural equation modelling (SEM) was utilised to analyse the data collected. The findings show that the purchasing preferences vary by product category. Reference Aaker, D.A., Kumar, V. and Day, G. (2006) Marketing Research, New York: Wiley. Armstrong, G. and Kotler, P. (2003) Marketing: An Introduction, Pearson Education International. Bakos, Y.J. (1997) 'Reducing Buyer Search Costs: Implications for Electronic Marketplaces', Management Science, vol. 43, no. 12, p. 1676–1692. Bellman, S., Lohse, G.L. and Johnson, E.J. (1999) 'Predictors of Online Buying Behavior', Communications of the ACM, vol. 42, no. 12, pp. 32-38. Bhatnagar, A., Misra, S. and Rao, R. (2000) 'On Risk, Convenience, and Internet Shopping Behavior', Communications of the ACM, vol. 43, no. 11, pp. 98-105. Blake, B.F., Neuendorf, K.A. and Valdiserri, C.M. (2003) 'Innovativeness and variety of internet shopping', Internet Research-Electronic Networking Applications and Policy, vol. 13, no. 3, pp. 156–169. Brown, S.A. and Venkatesh, V. (2005) 'Model of adoption of technology in household: A baseline model test and extension incorporating household life cycle', MIS Quarterly, vol. 29, no. 3, pp. 399–426. Brown, M., Pope, N. and Voges, K. (2003) 'Buying or browsing?: An exploration of shopping orientations and online purchase intention', European Journal of Marketing, vol. 37, no. 11/12, pp. 1666-1685. Burroughs, R.E. and Sabherwal, (2001) 'Determinants of retail electronic purchasing: a multi-period investigation', Journal of Information System Operation Research, vol. 40, no. 1, pp. 35-56. Chu, J., Arce-Urriza, M., Cebollada-Calvo, J.-J. and Chintagunta, P.K. (2010) 'An Empirical Analysis of Shopping Behavior Across Online and Offline Channels for Grocery Products: The Moderating Effects of Household and Product Characteristics', Journal of Interactive Marketing, vol. 24, pp. 251-268. Evolution (2012) Online Food and Grocery: The Shopper Perspective 2012, [Online], Available: HYPERLINK "http://de.slideshare.net/evolutioninsights/online-2012-sample-extract" http://de.slideshare.net/evolutioninsights/online-2012-sample-extract [07 June 2021]. Dholakia, R.R. and Uusitalo, O. (2002) 'Switching to electronic stores: Consumer characteristics and the perception of shopping benefit', International Journal of Retail & Distribution Management, vol. 30, no. 10, pp. 459–469. Donthu, N. and Garcia, A. (1999) 'The Internet Shopper', Journal of Advertising Research, vol. 39, no. 3, pp. 52-58. Garson. D. (2008). 'Structural Equation Modeling' from Statnotes: Topics in Multivariate Analysis. North Carolina State University, Retrieved August 15, 2014. http://www.statisticalassociates.com/assumptions.pdf Gefen, D., Straub, D. W., and Boudreau, M.-C. 2000. “Structural Equation Modeling and Regression: Guidelines for Research Practice,” Communications of the Association for Information Systems, vol. 4, no 7, pp. 1-70 Girard, T., Korgaonkar, P. and Silverblatt, R. (2003) 'Relationship of type of Product, shopping orientations, and demographics with preference for shopping on the internet', Journal of Business and Psychology, vol. 18, no. 1, pp. 101-120. Goldsmith, R.E. and Flynn, L.R. (2005) 'Bricks, clicks, and pix: Apparel buyers ’ use of stores, internet, and catalogs compared', International Journal of Retail & Distribution Management, vol. 33, no. 4, pp. 271–283. Hair, J. F., Jr., W. C. Black, B. J. Babin, and R. E. Anderson. (2010). Multivariate Data Analysis. 7th ed. Upper Saddle River, NJ: Pearson. Hansen, T. (2004) 'Consumer values, the theory of planned behaviour and online grocery shopping', International Journal of Consumer Studies, vol. 32, pp. 128-137. Haque, A., Mahmud, S.A., Tarofder, A.K. and Ismail, A.Z.H. (2007) 'Internet advertisement in Malaysia: A study on attitudinal differences', The Electronic Journal on Information Systems in Developing Countries, vol. 31, no. 9, pp. 1-15. Hasan, B. (2010) 'Exploring gender differences in online shopping attitude', Computers in Human Behavior, vol. 26, pp. 597–601. Hashim, A., Ghani, E.K. and Said, J. (2009) 'Does Consumers’ Demographic Profile Influence Online Shopping?: An Examination Using Fishbein’s Theory', Canadian Social Science, vol. 5, no. 6, pp. 19-31. Jarvenpaa, S.L. and Todd, P.A. (1997) 'Consumer Reactions to Electronic Shopping on the World Wide Web', International Journal of Electronic Commerce, vol. 1, no. 2, pp. 59–88. Joines, J.L., Scherer, C.W. and Scheufele, D.A. (2003) 'Exploring motivation for consumer web use and their implication for e-commerce', Journal of Consumer Marketing, vol. 20, no. 2, pp. 90-108. Kim, E.Y. and Kim, Y.K. (2004) 'Predicting online purchase intention for clothing products', European Journal of Marketing, vol. 38, no. 7, pp. 883–897. Kock, N. 2012. WarpPLS 3.0 user manual, Laredo, Texas, ScriptWarp ystems. Koyuncu, C. and Lien, D. (2003) 'E-commerce and consumer’s purchasing behaviour', Applied Economic, vol. 35, no. 6, pp. 721–726. Li, H., Kuo, C. and Rusell, M.G. (1999) 'The Impact of Perceived Channel Utilities, Shopping Orientations, and Demographics on the Consumer's Online Buying Behavior', Journal of Computer-Mediated Communication, vol. 5, no. 2. Lian, J.-W. and Lin, T.-M. (2008) 'Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types', Computers in Human Behavior, vol. 24, pp. 48-65. Liao, Z. and Cheung, M.T. (2001) 'Internet-based e-shopping and consumer attitudes: an empirical study', Information & Management, vol. 38, pp. 299-306. Lohse, G.L. and Spiller, P. (2000) 'Internet retail store design: how the user interface influences traffic and sales', Journal of Computer Mediated Communication, vol. 5, no. 2, pp. 219-234. Mahmood, M.A., Bagchi, K. and Ford, T.C. (2004) 'On-Line Shopping Behavior: Cross-Country Empirical Research', International Journal of Electronic Commerce, vol. 9, no. 1, pp. 9-30. Monsuwé, T.P., Dellaert, B.G.C. and de Ruyter, K. (2004) 'What drives consumer to shop online? A literature review', International Journal of Service Industry Management, vol. 15, no. 1, pp. 102-121. Netemeyer, R., Bearden, W. & Sharma, S. 2003. Scaling procedures: issues and applications, London, Sage Publications. Nielsen UK (2012) Marketing Magazine, [Online], Available: HYPERLINK "http://www.marketingmagazine.co.uk/article/1158155/uk-online-grocery-sales-surge-consumers-seek-value" http://www.marketingmagazine.co.uk/article/1158155/uk-online-grocery-sales-surge-consumers-seek-value [06 June 2021]. Sulaiman, A., Ng, J. and Mohezar, S. (2008) ' E-Ticketing as a new way of buying tickets: Malaysian perceptions', Journal of Social Science, vol. 17, no. 2, pp. 149-157. Susskind, A.M. (2004) 'Electronic Commerce and World Wide Web Apprehensiveness: An Examination of Consumers' Perceptions of the World Wide Web', Journal of Computer-Mediated Communication, vol. 9, no. 3. Rohm, A.J. and Swaminathan, V. (2004) 'A typology of online shoppers based on shopping motivations', Journal of Business Research, no. 57, pp. 748– 757. Zhou, L., Chiang, W.Y. and Zhang, D. (2004) 'Discovering Rules for Predicting Customers' Attitude Toward Internet Retailers', Journal of Electronic Commerce Research, vol. 5, no. 4, pp. 228-238.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil0,538

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,232
Tête enseignante GPT0,436
Écart entre enseignants0,204 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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Même revueZanco Journal of Humanity SciencesMême sujetTechnology Adoption and User BehaviourTravaux en français237 207