Exploring the impact of handset upgrades on mobile content and service usage

Sugai, Philip

doi:10.1504/ijmc.2007.012395

Cited by 25 publications

(13 citation statements)

References 34 publications

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“…Cooperation with mobile network operators makes it simpler to offer incentives, for instance, by providing invoice rebates or free SMS/MMS. A further conceivable incentive, the provision of mobile devices (Sugai, 2007), can help to mitigate technological gaps or to attract (selected) panel members. Dropout rates, which are usually only measured for internet surveys, are also impacted by incentives, personalisation, technical aspects and the length of the questionnaire.…”

Section: Mobile Surveysmentioning

confidence: 99%

Panel surveys go mobile

Weber

Denk²,

Oberecker³

et al. 2008

IJMC

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In order to take panel surveys into the 'mobile age', a careful analysis of their characteristics is conducted. Core issues of mobile surveys and panel designs are addressed and contrasted to their respective alternatives. Moreover, the use of mobile technology for carrying out panel surveys is discussed. Thereby, necessary actions and actors involved are identified, which provides a guideline for realising the potential of 'mobile panel surveys'. Essentially, the benefits are due to enhancements in the areas of survey quality, management and technology. The recommendations made can contribute to the development of a new business model in market research.

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Section: Mobile Surveysmentioning

confidence: 99%

Panel surveys go mobile

Weber

Denk²,

Oberecker³

et al. 2008

IJMC

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“…According to a study conducted in the UK, close to 40 percent of the youth market uses MMS (Enpocket, 2004). Similar literature has established a direct link between handset manufacturers and service providers within the overall mobile value chain (Sugai, 2007;Kim and Yoon, 2004;McBride 2003). The researchers explored factors influencing the adoption and usage of content and service sites via the mobile handset as well as the acceptance of mobile advertisement.…”

Section: Operator Services and Usagementioning

confidence: 82%

Brand Preference for Mobile Phone Operator Services in the Cape Coast Metropolis

Dadzie¹,

Boachie-Mensah²

2011

IJBM

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Branding is increasingly being used as a strategy for managing markets in developed countries while developing countries still lag behind. The objective of this study was to assess the level of brand awareness and factors underlying brand preference of mobile phone service brands in Cape Coast market in Ghana. A total of 100 respondents who included individual consumers were selected using accidental simple sampling technique. Primary data was collected using structured interview schedules developed for each category of consumers. The findings of the study showed that most of the respondent consumers were aware of mobile phone operator brands despite having come across few operator service advertisements. Young males, mainly students in the tertiary institutions, single and of Christian affiliations, dominated the market. Four factors were identified as key determinants of mobile phone operator service choice, namely promotion, price and availability of product, attractive packaging and product quality. There is need for mobile phone operators to incorporate these findings in the formulation of responsive marketing strategies.

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“…Further, a customer's IP traffic volume is affected by both the frequency and the duration of MI use cases. Compared to mobile customers' monthly bills for their IP traffic which Sugai (2007) employed to gauge MI use intensity, the traffic figure has two advantages: First, it is applicable across various MNO with different price schemes. Secondly, the metric is not distorted by customers' (in)ability to exactly select the MI tariff which best fits their typical use behaviors in the sense that it minimizes their monthly amount paid for MI and is therefore insensitive to customers' potential biases against or in favor of specific types of pricing schedules (cf., Verkasalo 2008b Table 2).…”

Section: Measurement Of MI Use Intensitymentioning

confidence: 99%

“…With regard to MI appliance class previous research suggests that mobile end-user devices' capabilities and usability of the human-machine interface have considerable impacts on the acceptance of diverse MI offerings (Carlsson et al 2005;Sugai 2007;Verkasalo 2008a). From a broad perspective, two classes of appliances for MI access are currently distinguishable (Smura et al 2009).…”

Section: Measurement Of Potential Determinants Of MI Use Intensitymentioning

confidence: 99%

“…Fewer post-adoption investigations construe their dependent MI or MDS acceptance measures from MNO customers' stated intensity, frequency and/or duration of certain categories of mobile communication behaviors such as running a video stream, browsing news websites, or employing a search machine portal (e.g., FogelgrenPedersen 2005;Sugai 2007;Turel et al 2007;Bina et al 2008;Economides and Grousopoulou 2008;Koivumäki et al 2008;Lee et al 2008;Oh et al 2008;Wei 2008;Westlund and Bohlin 2008;Bouwman et al 2009). The accuracy of customers' MI-related self-estimates of their use frequencies, duration, or changes must not be taken for granted.…”

mentioning

confidence: 99%

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Determinants of self-report and system-captured measures of mobile Internet use intensity

Gerpott

2010

Inf Syst Front

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Most research on the first adoption and subsequent use (= acceptance) of Internet access through cellular networks and portable appliances (= mobile Internet) has followed a similar pattern. It has employed survey responses of mobile network operator [MNO] customers to explain consumers' stated future use (continuance) intentions or claimed use intensities related to mobile Internet [MI] access by various beliefs about MI (e.g., perceived relative advantage, usefulness, ease of use). However, there is ample evidence suggesting that MI use intentions and self-reported use intensities are only weakly correlated with actual MI use. Therefore, the present paper develops hypotheses on how the ability of different types of variables to account for variance in MI use intensity may vary depending on whether subjectively estimated or objectively captured use serves as the criterion variable. The hypotheses are tested by analyzing actual MI use behaviors of 300 adopters in Germany, whose mobile IP traffic was extracted from an MNO's billing engine. This "system-captured" criterion measure is integrated with MI adopter responses collected by means of a standardized telephone survey. Results show that the predictors are more strongly correlated with self-rated than with system-captured MI use intensity. Up to 38% of the variance explained in selfrated use may be attributed to artifactual covariance between variables caused by common measurement methods. Factual MI use case features (MI tariff type and appliance class, fixed Internet home access availability) are better able to account for variance in both self-rated and actual MI use intensity than MI related beliefs. The findings imply that variable relationships observed in earlier MI and information system (IS) acceptance studies are likely to have been inflated by common method biases and thus may have provided spurious support for the conceptual frameworks tested. Implications of the results for future MI and IS acceptance research and for MNO seeking to forecast and to influence the MI use intensity of their customers are discussed.

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Exploring the impact of handset upgrades on mobile content and service usage

Cited by 25 publications

References 34 publications

Panel surveys go mobile

Panel surveys go mobile

Brand Preference for Mobile Phone Operator Services in the Cape Coast Metropolis

Determinants of self-report and system-captured measures of mobile Internet use intensity

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