Consumer reactions to crowded retail settings: Cross‐cultural differences between North America and the Middle East

Pons, Frank; Laroche, Michel; Mourali, Mehdi

doi:10.1002/mar.20146

Cited by 103 publications

(90 citation statements)

References 59 publications

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“…Tse et al (2002) argued that crowded restaurants were related to higher levels of reputation and perceived food quality. Pons et al (2006) confirmed that a crowded hedonic consumption setting could arouse a positive evaluation from customers.…”

Section: Research Hypotheses Testingmentioning

confidence: 57%

Waiting in line at a fashion store: psychological and emotional responses

Park

Min

Lee

2014

Fashion and Textiles

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Waiting in a service context is known to negatively affect consumer evaluation of services and service providers. However, this study investigates the positive effects of waiting-such as expected customer competition, excitement, and purchase intention-during the purchase of fashion merchandise. We classified waiting into four types based on whether waiting occurs, whether customers receiver a filler, or whether a filler is related to the context. A scenario-based online survey was conducted for empirical testing. After reading the scenario, 266 respondents replied to a questionnaire regarding expected competition, excitement, and purchase intention. The findings indicated that expected competition, excitement, and purchase intention differed significantly according to the wait type. Customers provided with a context-related filler reported the highest expected competition, excitement, and purchase intention, and excitement was found to mediate the relationship between expected competition and purchase intention. This paper ends by discussing its implications for managing waiting at a fashion store.

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Section: Research Hypotheses Testingmentioning

confidence: 57%

Waiting in line at a fashion store: psychological and emotional responses

Park

Min

Lee

2014

Fashion and Textiles

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“…Approaches have included: the presentation of photographs (Eroglu & Machleit, 1990;Ozdemir, 2008), video recordings (Smith et al, 2009), or slides (Eroglu & Machleit, 1990;Hui & Bateson, 1991) of different crowd environments, accompanied by written crowd scenarios read to participants in order to imagine being in the situation under investigation (Pons et al, 2006). However, it is unclear how far such methodologies initiate valid and reliable responses compared with actual experiences of being in a crowd.…”

Section: Methodology Used To Analyze Crowdingmentioning

confidence: 99%

“…Substantial research has been carried out concerning specific factors affecting the crowd experience, including: satisfaction of individuals in crowds (Baum & Greenberg, 1975;Altmans, 1975;Schmidt & Keating, 1979;Machleit, Eroglu & Mantel, 2000); performance of desired or necessary tasks (Klein & Harris, 1979); individual personality (Worchel & Teddie, 1976;Spacapan & Cohen, 1983); psychological reactions to a given crowd situation (Worchel & Yohai, 1979); prior expectations and experiences (Baum & Greenberg, 1975;Webb & Worchel, 1993) gender (Rustemli, 1992;Ozdemir, 2008) and culture (Pons, Laroche & Mourali, 2006;Pons & Laroche, 2007). Investigation has also focused on the contribution of different crowd situations to individual experience of stress (Cox, Houdmont & Griffiths, 2006) and personal space preferences (Hasse & Markey, 1973;Hayduk, 1983;Sinha & Sinha, 1991;Rustemli et al, 1992;Kaya & Erkip, 1999;Gerin-Lajoie, Richards & McFadyen, 2005;Evans & Wener, 2007;Martinez, 2009).…”

Section: Introduction Background Informationmentioning

confidence: 99%

The user experience of crowds -- A human factors challenge

Kendrick¹,

Haslam²

2010

PsycEXTRA Dataset

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Crowds are such an integral part of our everyday lives, yet research considering how the user experience of crowds can be enhanced, remains relatively underdeveloped. As with any other user interaction, the key human factors considerations of user safety, performance, comfort and satisfaction apply. A review of literature highlighted that important factors influencing the operation of crowds have been studied relatively independently, tending to focus on specific crowd situations, but rarely accounting for the interaction of factors and similarities and differences between crowd types. Focus groups exploring individual experiences of crowds revealed differences and priorities varying with age and expectations. This initial study contributes towards modeling contributory factors to the crowd experience, moving towards a more holistic understanding.

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“…It can also be reasonably assumed that agent interaction in activities infrastructure a ects travel choices (Axhausen, 2006). Marketing science provides ample evidence that agent interactions in uence utility (positively or negatively) of performing an activity (Baker et al, 1994, p.331), (Eroglu and Harrell, 1986;Eroglu and Machleit, 1990;Eroglu et al, 2005;Harrell et al, 1980;Hui and Bateson, 1991;Pons et al, 2006).…”

Section: Facility Loadmentioning

confidence: 99%

The Multi-Agent Transport Simulation MATSim

Axhausen¹

2016

500

123

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PrefaceDeveloping complex so ware for over a decade with a heterogeneous group of engineers and scientists, each with widely di erent skill levels and expertise across multiple locations around the world, requires dedication and mechanisms unusual for a university environment. This book is one of these mechanisms. It allows us, collectively, to take stock and present a coherent state-of-the-system: for us and anyone interested in this approach. It highlights basics for the student who wants to undertake a small rst research project as part of his or her degree, provides a description of the main functionalities, in detail, for the engineer setting up MATSim (MultiAgent Transport Simulation) to conduct a policy analysis and, nally, ts the approach into the theoretical background of complex systems in computer science and physics.The choice of the additional e-book format is an advantage, as it allows us to keep the book upto-date with future chapters, revisions and, if necessary, errata. Equally importantly it allows you, the readers, to select those sections relevant to your needs.The book comes at an important time for the system; for most of the rst decade, its use was limited to the original developers and users in Berlin and Zürich. It is now much more widely consulted around the world, as we document in the chapter summarizing contributions on scenarios so far.Scenario: This term will occur again and again. In MATSim context, it is de ned as the combination of speci c agent populations, their initial plans and activity locations (home, work, education), the network and facilities where, and on which, they compete in time-space for their slots and modules, i.e., behavioral dimensions, which they can adjust during their search for equilibrium. Within these scenarios, the user can experiment and explore with behavioral utility function parameters, with the sampling rate of the population between 1 % and 100 %, with algorithm parameters, e.g., the share of the sample engaged in replanning in any iteration, or behavioral dimensions or exact settings necessary to avoid gridlock due to the tra c ow dynamics. The creation of a scenario is a substantial e ort, and the framework makes a number of tools available to accelerate it: population synthesizers, network editors, network converters between popular formats and the MATSim representation, e.g., OSM (OpenStreetMap) or GTFS (General Transit Feed Speci cation), semi-automatic network matching to join information, among others.A large group of colleagues has been involved and many of them are contributors to this book; this is a list of those involved, other than ourselves, in Berlin, Singapore and Zürich. Additional contributors are mentioned as authors of their respective chapters in this book. We hope to acknowledge the contributions of more colleagues from other groups in future versions of this book and in the so ware.Special thanks go to a number of people who greatly helped improving this book beyond their own chapters. Benjamin Kickhöfer's deep knowledge of ...

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Consumer reactions to crowded retail settings: Cross‐cultural differences between North America and the Middle East

Cited by 103 publications

References 59 publications

Waiting in line at a fashion store: psychological and emotional responses

Waiting in line at a fashion store: psychological and emotional responses

The user experience of crowds -- A human factors challenge

The Multi-Agent Transport Simulation MATSim

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