Mobile phones and the evolution of social behaviour

Srivastava, Lara

doi:10.1080/01449290512331321910

Cited by 300 publications

(215 citation statements)

References 7 publications

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“…The pervasiveness of mobile phones in the daily routine of its users, render it the position of a social object, which is a shift from its earlier acquired technological status. 41 This service has gradually attained the status of another vital marketing communication channel, next to electronic and print media. A large number of companies have been observed to adopt sales promotion by sending discount coupons through mobile phone text messages, or through SMS (m-coupons).…”

Section: Discussionmentioning

confidence: 99%

An empirical analysis of customer loyalty in Pakistan's telecommunication industry

Jahanzeb¹,

Fatima²,

Khan³

2011

J Database Mark Cust Strategy Manag

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Section: Discussionmentioning

confidence: 99%

An empirical analysis of customer loyalty in Pakistan's telecommunication industry

Jahanzeb¹,

Fatima²,

Khan³

2011

J Database Mark Cust Strategy Manag

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“…Srivastava (2005) gives a rich overview of how the mobile phone has moved beyond being a simple technical device to becoming a key social object. In Belgium, the number of mobile phone subscribers has increased by 68% from 2000 to 2005.…”

Section: Data and Modelsmentioning

confidence: 99%

Integrated mixed logit and latent variable models

Danthurebandara

Vandebroek

2012

Mark Lett

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A traditional discrete choice model assumes that an individual's decision-making process is based on utility maximization and that the systematic part of the utility function depends on some observable attributes and covariates. These attributes and covariates however can only explain part of the utility and a large part remains unexplained. In recent years, researchers have recognized that psychological factors such as attitudes, lifestyle and values can a ect an alternative's utility and hence the individual's choices. Therefore, extending the traditional discrete choice model by incorporating those latent or unobservable factors, can help to better understand the individual's decision making process and therefore to yield more reliable part-worth estimates and market share predictions.Several integrated choice and latent variable (ICLV) models which merge the conditional logit model with a structural equation model exist in the literature. They assume homogeneity in the part-worths and use latent variables to model the heterogeneity among the respondents. The current research uses the mixed logit model that describes the heterogeneity in the part-worths and uses the latent variables to decrease the unexplained part of the heterogeneity. The empirical study that we conducted to assess student preferences on mobile phone features shows these ICLV models perform very well with respect to model t and prediction.Furthermore, we compare the di erent estimation procedures that exist in the literature. Results show that, as expected, the simultaneous procedure where we estimate the structural equation model (SEM) and the choice model simultaneously, gives better model t and more accurate predictions compared to the sequential procedure that estimates the SEM rst and then the choice model taking the estimated factor scores into account. But the gain of the simultaneous procedure is relatively small. Therefore one can use the easier sequential procedure without losing much e ciency if needed.

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“…Social impacts of mobile technology have been widely studied [12][13][14][15], especially the pervasive nature of mobile phones in public places. Most of the literature in this area focuses on the distraction of bystanders by people talking loudly on the phone or by the mix-up of geographic spaces (current physical space the mobile phone user is in and the space created by a phone conversation) [12,13,20]. In the case of using a mobile NSS, distraction is, of course, especially an issue when the NSS user is in an active, ongoing communication with the other negotiation party (face-to-face or on the phone).…”

Section: Related Workmentioning

confidence: 99%

Social Acceptance of Negotiation Support Systems

Pommeranz

Wiggers

Brinkman

et al. 2010

HCI in Work and Learning, Life and Leisure

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Abstract. We investigate people's attitudes towards the possible use of mobile negotiation support systems (NSS) in different social contexts and the consequences for their design. For that purpose we developed an online survey based on existing models of technology acceptance. In the questionnaire we showed five filmed scenarios of NSS use contexts. The data collected from 120 respondents, showed (a) that subjective norm is an important factor influencing the intention to use the system and (b) that the acceptance of NSS depends on the use context. Therefore, we argue that NSS should be designed not merely as tools being used in the actual negotiation but as social devices harnessing social networks to provide support in all negotiation phases.

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Mobile phones and the evolution of social behaviour

Cited by 300 publications

References 7 publications

An empirical analysis of customer loyalty in Pakistan's telecommunication industry

An empirical analysis of customer loyalty in Pakistan's telecommunication industry

Integrated mixed logit and latent variable models

Social Acceptance of Negotiation Support Systems

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