Shopping for fun or shopping to buy: Is it different online and offline?

Scarpi, Daniele; Pizzi, Gabriele; Visentin, Marco

doi:10.1016/j.jretconser.2014.02.007

Cited by 144 publications

(98 citation statements)

References 57 publications

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“…Babin et al (1994) proposed two experience value dimensions: hedonic and utilitarian. Hedonic value is related to enjoyment and playfulness, reflecting the experiential side of shopping, comprising pleasure and curiosity (Scarpi et al 2014). The main antecedent of hedonic value is the emotional experience (Jackson et al 2011).…”

Section: Value Perception Towards Shopping Experiencementioning

confidence: 99%

Living Positive Experiences in Store: How It Influences Shopping Experience Value and Satisfaction?

Cachero-Martínez

Vázquez‐Casielles

2017

Journal of Business Economics and Management

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Retailers have tried to differentiate themselves from their competitors through shopping experience. This is the first study analysing relationships between experience dimensions, shopping experience value and satisfaction. In this article different shopping experience dimensions are identified: emotional, sensory, intellectual, social, and pragmatic. In-depth interviews were conducted with a panel of experts to adapt a set of experience dimensions identified from the literature to the offline environment. A survey was then designed to collect data from consumers who had bought in a retailer, where marketing strategies are linked with experience dimensions. Retailers may use this typology in order to re-design their marketing strategies. Retailers must invest in utilitarian attributes of product assortment offered to consumers, improving quality while maintaining prices and promotions. If a retailer can stimulate social shopping and consumer curiosity, such as imagination and creativity in the store, they will have more devoted consumers.

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Section: Value Perception Towards Shopping Experiencementioning

confidence: 99%

Living Positive Experiences in Store: How It Influences Shopping Experience Value and Satisfaction?

Cachero-Martínez

Vázquez‐Casielles

2017

Journal of Business Economics and Management

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“…Chu et al (2010) find that grocery shoppers exhibit significant differences between online and offline shopping behaviors. Furthermore, online and offline shoppers express different content in word of mouth messages (Scarpi, Pizzi, and Visentin 2014). These findings demonstrate that consumers behave differently in those two shopping contexts and that consumers have different motivations for shopping online than for shopping offline.…”

Section: Introductionmentioning

confidence: 88%

Why do smartphone shoppers help others on websites? The effects of attachments on reciprocal altruism

Kim

Chung

Lee

et al. 2016

Information Development

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Why do people help others on mobile shopping sites, even when members have never met? To answer the research question, this study applies attachment theory to investigate the relationships between formation variables (trust, enjoyment, and timesaving), transfer variables (site, group, and interpersonal attachments), and an outcome variable (reciprocal altruism). An online survey was conducted of shoppers who had purchased tourism products with smartphones. The results show that trust, enjoyment, and timesaving have significant effects on site attachment, which, in turn, have a significant effect on both group and interpersonal attachments. Interpersonal attachment also has a highly significant effect on group attachment. Reciprocal altruism is influenced by both site and interpersonal attachments. The findings not only provide theoretical contributions to the tourism literature but also practical contributions to the tourism industry.

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“…Against this background, focusing on the online world when calculating the CLNV can only provide a limited view and may be insufficient in some cases. Therefore, we see the integrated quantification of both online and offline influence as a very promising topic for future research (Liu et al 2012;Scarpi et al 2014). This seems particularly challenging due to the fact that for the context of OSNs it is much easier to determine and estimate the customer specific parameters of the CLNV in an automated way (Tang and Guo 2015) (e.g., based on messages exchanged electronically and using text mining and sentiment analysis techniques and algorithms).…”

Section: Limitations and Further Researchmentioning

confidence: 94%

Customer lifetime network value: customer valuation in the context of network effects

Däs

Klier

et al. 2017

Electron Markets

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Nowadays customers are increasingly connected and extensively interact with each other using technologyenabled media like online social networks. Hence, customers are frequently exposed to social influence when making purchase decisions. However, established approaches for customer valuation mostly neglect network effects based on social influence. This leads to a misallocation of resources. Following a design-oriented approach, this paper develops a model for customer valuation referred to as the customer lifetime network value (CLNV) incorporating an integrated network perspective. By considering the customers' net contribution to the network, the CLNV reallocates values between customers based on social influence. Inspired by common prestige-and eigenvector-related centrality measures it incorporates social influence among all degrees of separation acknowledging its viral spread. Using a real-world dataset, we demonstrate the practicable applicability of the CLNV to determine individual customers' value.

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Shopping for fun or shopping to buy: Is it different online and offline?

Cited by 144 publications

References 57 publications

Living Positive Experiences in Store: How It Influences Shopping Experience Value and Satisfaction?

Living Positive Experiences in Store: How It Influences Shopping Experience Value and Satisfaction?

Why do smartphone shoppers help others on websites? The effects of attachments on reciprocal altruism

Customer lifetime network value: customer valuation in the context of network effects

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