Untitled

Fennell, Geraldine; Allenby, Greg M.; Yang, Sha; Edwards, Yancy

doi:10.1023/a:1024686630821

Cited by 61 publications

(8 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study used two theoretical approaches to understand the short- and long-term motives behind fruit consumption. Contextual motivations focused on short-term motives using attributes and situational benefits (Fennell et al. , 2003; Fennell and Allenby, 2013), whereas transituational benefits focused on the long-term motives that encompassed emotions and human values (Gutman, 1982; Schwartz, 2017).…”

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

“…This is an original theoretical path because it merges the two approaches of contextual motivations and the MEC model. The first recognises short-term observable product characteristics (Fennell et al, 2003;Fennell and Allenby, 2013), whereas the latter works on long-term goals, emotions (Gutman, 1982) and human values (Schwartz, 2017). The path reveals meaningful reasons for understanding the consumers' involvement and long-term adoption of healthy eating habits.…”

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

See 1 more Smart Citation

The spirit of the fruit: contextual and transituational motives for consumption

Arboleda

Manfredi

Marcazzo

et al. 2023

BFJ

View full text Add to dashboard Cite

PurposeThis research aims to reach meaningful insights into fruit consumption motives. The study articulates contextual motives observed through inherent fruit characteristics (i.e. attributes and benefits) with personal motives that transcend the situation (i.e. emotions and cultural values).Design/methodology/approachThis qualitative study used the focus group technique comprising eight groups of eight to 10 subjects (n = 94). The participants were frequent fresh-fruit consumers.FindingsThe analysis differentiates contextual motives from transituational ones. Older participants are motivated by taking care of health matters. They value fruit as an expression of their determination to take action and care for others. Younger participants are motivated by the experience of pleasure. Fruits have a hedonic value related to joy, being refreshing and tasteful.Practical implicationsResults serve marketers and decision-makers to better target motivations for fruit consumption enhancement. These motivations could be implemented by communicating specific fruit attributes that respond to short-term needs. In the long run, marketers could create fruit consumption campaigns that respond to deeper consumer values.Social implicationsDesigning fruit consumption campaigns aligned with individuals' motives could effectively strengthen the adoption of a healthy lifestyle. This study is helpful from the aspect of a public-policy approach expected to improve public health.Originality/valueConsumers' fruit preference transcends tangible product characteristics to motives aligned with their goals, emotions and human values. This path merges two approaches: contextual motivations and the Means-end chain model. The first approach recognises short-term observable product characteristics, whereas the latter works on long-term values.

show abstract

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

The spirit of the fruit: contextual and transituational motives for consumption

Arboleda

Manfredi

Marcazzo

et al. 2023

BFJ

View full text Add to dashboard Cite

show abstract

“…Efficient document storage and retrieval for many institutions of learning have been noted to be one of the important applications of clustering. In addition, discovering events and sub-events from a sequence of news articles Rasmussen ( 1992 ), Piernik et al ( 2015 ), Chan et al ( 2016 ), Lee et al ( 2020 ), Celardo and Everett ( 2020 ) Image segmentation This is centered around the partition of images for visibility and classification of images based on some properties Forsyth and Ponce ( 2002 ), Lam and Wunsch ( 2014 ), Zhang et al ( 2020 ) Object recognition 3D object grouping has been an area of application Dorai and Jain ( 1995 ) Character recognition handwriting recognition has been an important application Connell and Jain ( 1998 ) Data mining Widely used in this field both to analyze structured and unstructured databases Hedberg ( 1996 ), Han et al ( 2011 ) Spatial and space application Large data sets from geographical information systems and satellite images have been analyzed using clustering techniques Upton and Fingleton ( 1985 ), Tahmasebi et al ( 2012 ), Song et al ( 2020 ), Zhang et al ( 2020 ) Business analytics Operational areas of marketing, demand management and production areas of product development and categorization Kiang et al ( 2007 ), Fennell et al ( 2003 ), Pereira and Frazzon ( 2020 ) Data reduction Compression of large data into manageable sizes usually saves processing time and cost Jiang et al ( 2016 ), Huang ( 1997 ) …”

Section: Applications Of Clusteringmentioning

confidence: 99%

Data clustering: application and trends

Oyewole

Thopil

2022

Artif Intell Rev

View full text Add to dashboard Cite

Clustering has primarily been used as an analytical technique to group unlabeled data for extracting meaningful information. The fact that no clustering algorithm can solve all clustering problems has resulted in the development of several clustering algorithms with diverse applications. We review data clustering, intending to underscore recent applications in selected industrial sectors and other notable concepts. In this paper, we begin by highlighting clustering components and discussing classification terminologies. Furthermore, specific, and general applications of clustering are discussed. Notable concepts on clustering algorithms, emerging variants, measures of similarities/dissimilarities, issues surrounding clustering optimization, validation and data types are outlined. Suggestions are made to emphasize the continued interest in clustering techniques both by scholars and Industry practitioners. Key findings in this review show the size of data as a classification criterion and as data sizes for clustering become larger and varied, the determination of the optimal number of clusters will require new feature extracting methods, validation indices and clustering techniques. In addition, clustering techniques have found growing use in key industry sectors linked to the sustainable development goals such as manufacturing, transportation and logistics, energy, and healthcare, where the use of clustering is more integrated with other analytical techniques than a stand-alone clustering technique.

show abstract

“…Sociodemographic characteristics are therefore not able to explain consumers' choices between national brands and private labels (Cataluña, García, & Phau, 2006). Using past research results for both for sociodemographic and psychographic characteristics, Fennell, Allenby, Yang, & Edwards (2003) conclude: "Since the early seventies, it has been known that the relationship between demographic and general psychographic variables and product use is present but not strong. The search for correlates for relative brand preference (e.g., using scanner data) has been less successful, with results suggesting that demographic and general psychographic variables are generally not predictive of brand use" (p. 241).…”

Section: Sociodemographicsmentioning

confidence: 99%

Proliferation of Private Labels in Food Retailing: A Literature Overview

Olbrich¹,

Hundt²,

Jansen³

2016

IJMS

View full text Add to dashboard Cite

This article provides an overview of private-label research by focusing on the food retailing sector. To explain the proliferation of private labels, we identify key drivers by reviewing the determinants discussed in prior literature. This article identifies the conditions that support the proliferation of private labels-retailer concentration and retailer pricing autonomy-and describes the nature of competition between private labels and national brands. It also highlights the drivers of private-label purchases by providing an overview of brand-related determinants, price and risk-related determinants, quality aspects, sociodemographics, and consumer purchasing behavior. The article concludes by proposing three areas for future private-label research.

show abstract

Untitled

Cited by 61 publications

References 35 publications

The spirit of the fruit: contextual and transituational motives for consumption

The spirit of the fruit: contextual and transituational motives for consumption

Data clustering: application and trends

Proliferation of Private Labels in Food Retailing: A Literature Overview

Contact Info

Product

Resources

About