A Contribution to Theory Building for Mobile Marketing: Categorizing Mobile Marketing Campaigns through Case Study Research

Marketing experts consider the mobile device as an extremely promising marketing tool as it supports them to cope with their major challenge: getting time and attention from customers. Current mobile marketing research mostly covers success factors and acceptance analysis. Categorization, when addressed, lacks in appropriate foundation and is not linked to objectives at all. In this article we examine 55 case studies in order to identify relevant characteristics of mobile marketing campaigns. The outcome of the paper is the derivation of four mobile marketing standard types and an examination of campaign objectives that can be addressed by mobile marketing. The proposed scheme allows to unambiguously characterize any given mobile marketing campaign and to identify the respective objectives.

MOBILE MARKETING FUTURE TRENDS

The present article proposes an introspection into the field of a new marketing specialization – mobile marketing. The concept mainly refers to all marketing activities related to the new communication channel – Short Message Service, Multimedia Messaging Service, and internet access from mobile phone. The article provides, at the same time, a marketing perspective about future trends of mobile marketing and mobile media, and also a technical perspective related to the future mobile communication technologies in the field – the LTE (Long Term Evolution) – cellular communication system optimized to support packet-switched data services to enable mobile broadband. The conclusions of the article focus on the relevance of mobile marketing, techniques efficiency related to brand promotion, changing consumers attitude and the development of such techniques imposed by the new mobile communication systemmobile marketing; long term evolution; broadband; brand awareness; consumer attitude

Interaction effects on prediction of children weight at school entry using model averaging

Model selection introduce uncertainty to the model building process, therefore model averaging was introduced as an alternative to overcome the problem of underestimate of standards error in model selection. This research also focused on using selection criteria between Corrected Akaike's Information Criteria (AICC) and Bayesian Information Criteria (BIC) as weight for model averaging when involving interaction effects. Mean squared error of prediction (MSE(P)) was used in order to determine the best model for model averaging. Gateshead Millennium Study (GMS) data on children weight used to illustrate the comparison between AICC and BIC. The results showed that model selection criterion AICC performs better than BIC when there are small sample and large number of parameters included in the model. The presence of interaction variable in the model is not significant compared to the main factor variables due to the lower coefficient value of interaction variables. In conclusion, interaction variables give less information to the model as it coefficient value is lower than main factor

Structural equation modeling of eBankQual scale: a study of E-Banking in India

This study assesses the relationship between perceived quality, brand perception and perceived value with satisfaction. For the data analysis structural equation modeling (SEM) method and path analysis method were used. A result indicates that, eBankQual model is fit to assess relationship between service quality, brand perception and perceived value with overall customers’ satisfaction in e-banking service. Result of regression SEM indicates that, all 14 variables found significant and good predictors of overall satisfaction in e-banking services. However, result of SEM analysis indicates that, data supports to eBankQual model and dimensions Compensation, Convenience, Contact Facilities, Easy to Use, Responsiveness, Cost Effectiveness and System Availability including brand perception and perceived value were found more significant factors in the eBankQual model.Structural Equation Modeling, Service quality, Brand perception, Perceived value, Satisfaction

The impact of different touchpoints on brand consideration

Marketers face the challenge of resource allocation across a range of touchpoints. Hence understanding their relative impact is important, but previous research tends to examine brand advertising, retailer touchpoints, word-of-mouth, and traditional earned touchpoints separately. This article presents an approach to understanding the relative impact of multiple touchpoints. It exemplifies this approach with six touchpoint types: brand advertising, retailer advertising, in-store communications, word-of-mouth, peer observation (seeing other customers), and traditional earned media such as editorial. Using the real-time experience tracking (RET) method by which respondents report on touchpoints by contemporaneous text message, the impact of touchpoints on change in brand consideration is studied in four consumer categories: electrical goods, technology products, mobile handsets, and soft drinks. Both touchpoint frequency and touchpoint positivity, the valence of the customer's affective response to the touchpoint, are modeled. While relative touchpoint effects vary somewhat by category, a pooled model suggests the positivity of in-store communication is in general more influential than that of other touchpoints including brand advertising. An almost entirely neglected touchpoint, peer observation, is consistently significant. Overall, findings evidence the relative impact of retailers, social effects and third party endorsement in addition to brand advertising. Touchpoint positivity adds explanatory power to the prediction of change in consideration as compared with touchpoint frequency alone. This suggests the importance of methods that track touchpoint perceptual response as well as frequency, to complement current analytic approaches such as media mix modeling based on media spend or exposure alone

A sustainable village phone model to serve the rural developing world

Wireless technologies have created an unprecedented opportunity for rural customers in the developing world to solve their communication and information problems in an instantaneous, interactive and customized way. The framework of the study focuses on existing mobile village phone model in Bangladesh and suggests ways to make it sustainable through mobile information services marketing. The study has treated ‘village phone’ as a cost effective and interactive channel through which various time befitting information can be marketed to serve customers in the rural settings

Factors influencing students' acceptance of m-learning: An investigation in higher education

M-learning will play an increasingly significant role in the development of teaching and learning methods for higher education. However, the successful implementation of m-learning in higher education will be based on users' acceptance of this technology. Thus, the purpose of this paper is to study the factors that affect university students' intentions to accept m-learning. Based on the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors that influence the acceptance of m-learning in higher education and to investigate if prior experience of mobile devices affects the acceptance of m-learning. A structural equation model was used to analyse the data collected from 174 participants. The results indicate that performance expectancy, effort expectancy, influence of lecturers, quality of service, and personal innovativeness were all significant factors that affect behavioural intention to use m-learning. Prior experience of mobile devices was also found to moderate the effect of these constructs on behavioural intention. The results of this research extend the UTAUT in the context of m-learning acceptance by adding quality of service and personal innovativeness to the structure of UTAUT and provide practitioners and educators with useful guidelines for designing a successful m-learning system

Innovation Initiatives in Large Software Companies: A Systematic Mapping Study

To keep the competitive advantage and adapt to changes in the market and technology, companies need to innovate in an organised, purposeful and systematic manner. However, due to their size and complexity, large companies tend to focus on maintaining their business, which can potentially lower their agility to innovate. This study aims to provide an overview of the current research on innovation initiatives and to identify the challenges of implementing the initiatives in the context of large software companies. The investigation was performed using a systematic mapping approach of published literature on corporate innovation and entrepreneurship. Then it was complemented with interviews with four experts with rich industry experience. Our study results suggest that, there is a lack of high quality empirical studies on innovation initiative in the context of large software companies. A total of 7 studies are conducted in such context, which reported 5 types of initiatives: intrapreneurship, bootlegging, internal venture, spin-off and crowdsourcing. Our study offers three contributions. First, this paper represents the map of existing literature on innovation initiatives inside large companies. The second contribution is to provide an innovation initiative tree. The third contribution is to identify key challenges faced by each initiative in large software companies. At the strategic and tactical levels, there is no difference between large software companies and other companies. At the operational level, large software companies are highly influenced by the advancement of Internet technology. Large software companies use open innovation paradigm as part of their innovation initiatives. We envision a future work is to further empirically evaluate the innovation initiative tree in large software companies, which involves more practitioners from different companies