Mobile marketing in the 21st century: a partial least squares structural equation modelling approach

Pan, Vic Qi; Chew, Pai Qin; Cheah, Amy Shun Gui; Wong, Choy Har; Tan, Garry Wei–Han

doi:10.1504/ijmom.2015.072669

Cited by 13 publications

(8 citation statements)

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“…These results describe an impact of EE on PEOU while the impact of EE on BI was rejected. The association of EE and BI was also supported by literature in [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 81 ]. The reason behind the non-significant influence of EE on BI might be that the digital persons were native to the digital technology as they were born and grew up in the latest technologies.…”

Section: Resultssupporting

confidence: 79%

“…This relationship consequently influences perceived difficulty in using the system by its users. A positive association between EE and BI has been identified in the context of mobile technologies, particularly in mobile payment [ 68 ] and mobile marketing [ 69 ]. In the context of a mobile tourism application, a positive link was found between EE and BI [ 70 ].…”

Section: Proposed Model and Hypothesesmentioning

confidence: 99%

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Ride or Not to Ride: Does the Customer Deviate toward Ridesharing?

Shamim

Khan

Qureshi

et al. 2021

IJERPH

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Traditional taxi services have now been transformed into e-hailing applications (EHA) such as Uber, Careem, Hailo, and Grab Car globally due to the proliferation of smartphone technology. On the one hand, these applications provide transport facilities. On the other hand, users are facing multiple issues in the adoption of EHAs. Despite problems, EHAs are still widely adopted globally. However, a sparse amount of research has been conducted related to EHAs, particular in regards to exploring the significant factors of intention behind using EHAs Therefore, there is a need to identify influencing factors that have a great impact on the adoption and acceptance of these applications. Hence, this research aims to present an empirical study on the factors influencing customers’ intentions towards EHAs. The Technology Acceptance Model (TAM) was extended with four external factors: perceived mobility value, effort expectancy, perceived locational accuracy, and perceived price. A questionnaire was developed for the measurement of these factors. A survey was conducted with 211 users of EHAs to collect data. Structural equation modeling (SEM) was used to analyze the collected data. The results of this study exposed that perceived usefulness, perceived price, and perceived ease of use affect behavior intention to use EHAs. Furthermore, perceived ease of use was impacted by effort expectancy, perceived locational accuracy, and perceived mobility. The findings of the study provide a foundation to develop new guidelines for such applications that will be beneficial for developers and designers of these applications.

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Section: Resultssupporting

confidence: 79%

Section: Proposed Model and Hypothesesmentioning

confidence: 99%

Ride or Not to Ride: Does the Customer Deviate toward Ridesharing?

Shamim

Khan

Qureshi

et al. 2021

IJERPH

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“…The approach is similar to the study on adoption of mobile social media advertising in receiving tourism-related advertisements in Malaysia (Tan et al, 2018). Klang Valley was chosen because it is the main hub for business and the center of economics in Malaysia (Pan et al, 2015). Prior to distribution, pre-qualifying questions were asked to check if respondents have experience to use eco-labeled products.…”

Section: Methodsmentioning

confidence: 99%

Applying innovation attributes to predict purchase intention for the eco-labeled products

Choshaly

2019

IJIS

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Purpose This paper aims to make use of the innovation diffusion theory to predict the purchase intention for eco-labeled products. Design/methodology/approach Data are collected from 180 individuals in the Mid Valley shopping mall area in Malaysia. It is then analyzed using SPSS and Smart PLS. The measurement model is analyzed using composite reliability, convergent and discriminate validity, while the structural model is used to predict the relationships between variables. Findings Results indicate that the relative advantage, trialability and observability are positively related to eco-labeled products purchase intention, while the complexity is negatively related to eco-labeled products purchase intention. However, compatibility is not positively related to eco-labeled products purchase intention. Practical implications Marketers should enhance the observability of eco-labeled as it is the most influential attribute affecting eco-labeled products purchase intention. Relative advantages of eco-labeled products are also important to stimulate purchase intention. Marketers could best relate the innovation to context-specific use situations enabling consumers to evaluate the use consequences of the innovation, and therefore, may assess its particular benefits. Originality/value It explores the potential of a theoretical framework based on innovation diffusion theory to explain eco-labeled products purchase intention.

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“…The TAM is extended to get a better understanding of the user behavior on a proposed automated system [40]. The following internal variables were included in the proposed work by extending TAM [41] as shown in Figure 7. i. PUS: PUS is defined as the degree to which a User trusts using a particular system improves the job performance.…”

Section: Tam For User Acceptance Of the Proposed Methods Of User Idmentioning

confidence: 99%

Automated User Authentication in Wireless Public Key Infrastructure for Mobile Devices Using Aadhar Card

Prakash¹,

Muniyal²,

Acharya³

2019

IEEE Access

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Identification and authentication play a significant role in security controls. The manual process of user identification and authentication is time-consuming and tedious. The proposed research work aims to overcome this drawback and achieve user identification and authentication through an automated method using the Aadhar card. Aadhar project is developed by the Unique Identification Authority of India by merging biometrics and digitization. The details are stored in the form of a quick response code along with a 12-digit Aadhar card number. A model is built to capture the information from the Aadhar card. The mobile phones are used to obtain the data from the Aadhar card. The user validation is through twostep process using One Time Password and email address. The wireless public key infrastructure issues a digital certificate to the valid user. The proposed authentication and symmetric key exchange algorithm are formally verified and analyzed using automated validation of Internet security protocols and applications. The result of simulation proves that the proposed scheme is secure and safe. The experimental results show that time consumption for user authentication is acceptable. The acceptance of the proposed automated user identification and authentication model is authorized using a modified technology acceptance model. The result proves that there exists a strong relationship between the perceived usefulness of items and the Attribute Of Use (AOU). It also exhibits that the association between the AOU and user satisfaction is influential. The model demonstrates that the association between the Perceived Ease Of Use and attribute towards use is weak. The influence of exogenous variables over endogenous variables exhibits that the proposed model outperforms the traditional manual system and the target users are inclined towards it. The proposed model also finds its application in services which requires user authentication.

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Mobile marketing in the 21st century: a partial least squares structural equation modelling approach

Cited by 13 publications

References 0 publications

Ride or Not to Ride: Does the Customer Deviate toward Ridesharing?

Ride or Not to Ride: Does the Customer Deviate toward Ridesharing?

Applying innovation attributes to predict purchase intention for the eco-labeled products

Automated User Authentication in Wireless Public Key Infrastructure for Mobile Devices Using Aadhar Card

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