IDEAS home Printed from https://ideas.repec.org/a/sae/vikjou/v42y2017i4p234-250.html
   My bibliography  Save this article

Predicting Indian Shoppers’ Malls Loyalty Behaviour

Author

Listed:
  • Sanjeev Prashar
  • Harvinder Singh
  • Chandan Parsad
  • T. Sai Vijay

Abstract

Executive Summary Mall managers tend to believe that purchasing decisions are made inside the shopping malls. These decisions, however, are influenced by various antecedent factors. This implies that shoppers look beyond the basic chore of shopping and experience while shopping plays a vital role. To attract the attention of shoppers, mall developers make huge investments in mall promotion and ambient factors in order to enhance the shopping experience. As the Indian shoppers’ euphoria about shopping malls gets toned down with time, mall managers need to focus on something more substantive. Such fundamental benefits can be offered to shoppers only if mall managers know what is more relevant for the shoppers visiting the malls. Past studies have identified a number of factors such as ambience, physical infrastructure, convenience, safety, and marketing activities. This research posits that a more optimal and focused approach in mall management requires identification of relative significance of various influencing factors. This way, mall managers would be able to offer the most meaningful benefits to shoppers at a very optimal level of investment. Once shoppers get what they value the most, they are expected to be more loyal to the shopping mall. Despite the development of various forecasting techniques, predicting mall loyalty has remained under-explored in marketing literature. This article addresses the gap by using neural network model to predict shoppers’ loyalty towards a particular mall. To gain more insights from the model, the authors have also identified relative significance of the factors impacting shoppers’ mall selection. This study establishes that mall shoppers value ‘convenience’ as the most influencing factor in their selection of malls. This factor alone garners one-third of the total weightage among the five factors, which reflects that significance of convenience is 66 per cent more than what is expected in a scenario when all determinants contribute equally. This strongly indicates that Indian mall shoppers are more utilitarian than hedonic.

Suggested Citation

  • Sanjeev Prashar & Harvinder Singh & Chandan Parsad & T. Sai Vijay, 2017. "Predicting Indian Shoppers’ Malls Loyalty Behaviour," Vikalpa: The Journal for Decision Makers, , vol. 42(4), pages 234-250, December.
  • Handle: RePEc:sae:vikjou:v:42:y:2017:i:4:p:234-250
    DOI: 10.1177/0256090917731431
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0256090917731431
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0256090917731431?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hruschka, Harald, 1993. "Determining market response functions by neural network modeling: A comparison to econometric techniques," European Journal of Operational Research, Elsevier, vol. 66(1), pages 27-35, April.
    2. Babin, Barry J & Darden, William R & Griffin, Mitch, 1994. "Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(4), pages 644-656, March.
    3. Spangenberg, Eric R. & Grohmann, Bianca & Sprott, David E., 2005. "It's beginning to smell (and sound) a lot like Christmas: the interactive effects of ambient scent and music in a retail setting," Journal of Business Research, Elsevier, vol. 58(11), pages 1583-1589, November.
    4. Lowry, James R., 1997. "The life cycle of shopping centers," Business Horizons, Elsevier, vol. 40(1), pages 77-86.
    5. Babin, Barry J. & Hardesty, David M. & Suter, Tracy A., 2003. "Color and shopping intentions: The intervening effect of price fairness and perceived affect," Journal of Business Research, Elsevier, vol. 56(7), pages 541-551, July.
    6. Srivastava, Mala & Kaul, Dimple, 2014. "Social interaction, convenience and customer satisfaction: The mediating effect of customer experience," Journal of Retailing and Consumer Services, Elsevier, vol. 21(6), pages 1028-1037.
    7. Jackson, Vanessa & Stoel, Leslie & Brantley, Aquia, 2011. "Mall attributes and shopping value: Differences by gender and generational cohort," Journal of Retailing and Consumer Services, Elsevier, vol. 18(1), pages 1-9.
    8. Hui, Michael K & Bateson, John E G, 1991. "Perceived Control and the Effects of Crowding and Consumer Choice on the Service Experience," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(2), pages 174-184, September.
    9. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    10. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    11. Lunardo, Renaud, 2012. "Negative effects of ambient scents on consumers’ skepticism about retailer’s motives," Journal of Retailing and Consumer Services, Elsevier, vol. 19(2), pages 179-185.
    12. Sanjeev Prashar & Chandan Parsad & T. Sai Vijay, 2015. "Factors prompting impulse buying behaviour - study among shoppers in India," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 11(2), pages 219-244.
    13. Singh, Harvinder & Prashar, Sanjeev, 2014. "Anatomy of shopping experience for malls in Mumbai: A confirmatory factor analysis approach," Journal of Retailing and Consumer Services, Elsevier, vol. 21(2), pages 220-228.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhenxing Zhu & Wonjun Chung, 2023. "Enhancing Shoppers’ Experiences and Building Mall Loyalty: The Role of Octomodal Mental Imagery (OMI) and Management Dimension-Evidence from the Yangtze River Delta Region of China," Sustainability, MDPI, vol. 15(14), pages 1-24, July.
    2. Norlaile Salleh Hudin & Nur Shafiqa Azrin Khairil Annuar & Ahmad Zainal Abidin Abd Razak, 2019. "The Influence of Hedonic and Utilitarian Shopping Value Towards Consumer Behavioral Intention Among Youth Mall Shoppers," Research in World Economy, Research in World Economy, Sciedu Press, vol. 10(5), pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massara, Francesco & Liu, Sandra S. & Melara, Robert D., 2010. "Adapting to a retail environment: Modeling consumer-environment interactions," Journal of Business Research, Elsevier, vol. 63(7), pages 673-681, July.
    2. Qi, Min & Yang, Sha, 2003. "Forecasting consumer credit card adoption: what can we learn about the utility function?," International Journal of Forecasting, Elsevier, vol. 19(1), pages 71-85.
    3. El-Adly, Mohammed Ismail & Eid, Riyad, 2016. "An empirical study of the relationship between shopping environment, customer perceived value, satisfaction, and loyalty in the UAE malls context," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 217-227.
    4. Errajaa, Karim & Hombourger-Barès, Sabrina & Audrain-Pontevia, Anne-Françoise, 2022. "Effects of the in-store crowd and employee perceptions on intentions to revisit and word-of-mouth via transactional satisfaction: A SOR approach," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    5. Kwon, Ryeok-Hwan & Kim, Kwang-Jae & Kim, Ki-Hun & Hong, Yoo-Suk & Kim, Bohyun, 2015. "Evaluating servicescape designs using a VR-based laboratory experiment: A case of a Duty-free Shop," Journal of Retailing and Consumer Services, Elsevier, vol. 26(C), pages 32-40.
    6. Esbjerg, Lars & Jensen, Birger Boutrup & Bech-Larsen, Tino & de Barcellos, Marcia Dutra & Boztug, Yasemin & Grunert, Klaus G., 2012. "An integrative conceptual framework for analyzing customer satisfaction with shopping trip experiences in grocery retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 19(4), pages 445-456.
    7. Gupta, Ashish & Mishra, Vaibhav & Tandon, Anushree, 2020. "Assessment of Shopping Mall Customers’ Experience through Criteria of Attractiveness in Tier-II and Tier-III Cities of India: An Exploratory Study," American Business Review, Pompea College of Business, University of New Haven, vol. 23(1), pages 70-93, May.
    8. Lo, Ada & Qu, Hailin, 2015. "A theoretical model of the impact of a bundle of determinants on tourists’ visiting and shopping intentions: A case of mainland Chinese tourists," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 231-243.
    9. Turner, Frances & Merle, Aurélie & Gotteland, David, 2020. "Enhancing consumer value of the co-design experience in mass customization," Journal of Business Research, Elsevier, vol. 117(C), pages 473-483.
    10. Al-Kilani, Shaymaa & El Hedhli, Kamel, 2021. "How do restaurant atmospherics influence restaurant authenticity? An integrative framework and empirical evidence," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    11. Vivek Devvrat Singh & Utkal Khandelwal & Ankit Saxena, 2023. "Measuring Emotional Response from the Mall Experiences: A Case of Tier II and III City Malls in India," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 9(1), pages 118-135.
    12. Sabina Lissitsa & Ofrit Kol, 2021. "Four generational cohorts and hedonic m-shopping: association between personality traits and purchase intention," Electronic Commerce Research, Springer, vol. 21(2), pages 545-570, June.
    13. Thomas, Veronica L. & Saenger, Christina, 2020. "Feeling excluded? Join the crowd: How social exclusion affects approach behavior toward consumer-dense retail environments," Journal of Business Research, Elsevier, vol. 120(C), pages 520-528.
    14. Pranay Verma, 2013. "Framework For Music As Store Atmospherics To Induce Buying: A Study Of Delhi Mall Customers," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 81-100.
    15. Parsad, Chandan & Prashar, Sanjeev & Vijay, T. Sai & Kumar, Mukesh, 2021. "Do promotion and prevention focus influence impulse buying: The role of mood regulation, shopping values, and impulse buying tendency," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    16. Zielke, Stephan & Toporowski, Waldemar, 2012. "Negative price-image effects of appealing store architecture: Do they really exist?," Journal of Retailing and Consumer Services, Elsevier, vol. 19(5), pages 510-518.
    17. Hu, Michael Y. & Zhang, G. Peter & Chen, Haiyang, 2004. "Modeling foreign equity control in Sino-foreign joint ventures with neural networks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 729-740, December.
    18. Khan, Imran & Rahman, Zillur, 2015. "Brand experience anatomy in retailing: An interpretive structural modeling approach," Journal of Retailing and Consumer Services, Elsevier, vol. 24(C), pages 60-69.
    19. Vieira, Valter Afonso, 2013. "Stimuli–organism-response framework: A meta-analytic review in the store environment," Journal of Business Research, Elsevier, vol. 66(9), pages 1420-1426.
    20. Gruca, TS & Klemz, BR, 1998. "Using Neural Networks to Identify Competitive Market Structures from Aggregate Market Response Data," Omega, Elsevier, vol. 26(1), pages 49-62, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:vikjou:v:42:y:2017:i:4:p:234-250. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.