Analysis of consumer preferences for prepaid mobile internet packages in Iran: A Discrete Choice Experiment

Sohrabi, Arya; Pishvaee, Mir Saman; Hafezalkotob, Ashkan; Bamdad, Shahrooz

doi:10.20885/ejem.vol12.iss1.art4

Cited by 3 publications

(2 citation statements)

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“…Social capital emphasizes the positive effects of social activities and acts as an important aspect of nonmonetary capital. 30 51 However, many people connect to the Internet via their mobile data connection rather than home Internet. 52 This seems to be a challenge in developing 4P.…”

Section: Discussionmentioning

confidence: 99%

Public-Private-People Partnerships (4P) for Improving the Response to COVID-19 in Iran

Seddighi

Salmani

et al. 2020

Disaster med. public health prep.

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The Public–Private–People partnership (4P) is a significant element in disaster response. Coronavirus disease (COVID-19) as a pandemic has been the worst disaster in the last decades in Iran in terms of exposure and magnitude. In order to respond effectively, the Iranian Government needs an extra capacity, which may be provided by the private sector and people. This study aims to collect evidences of 4P pertaining to the COVID-19 response in Iran from February to April 2020. Partnership case studies are classified into 3 categories: (1) Public–private partnerships; (2) public–people partnerships; and (3) private–people partnerships. It was found that the Iranian Government has removed or diminished some of the barriers to cooperation. There was also more cooperation between the people, the private sector, and the public sector than during normal times (vs disasters). People participated in the response procedure through some associations or groups, such as religious and ethnic communities, as well as through non-governmental organizations. It has been shown that 4P is vital in disaster response and, in particular, to epidemics. The government can be more active in partnerships with the private sector and people in emergencies, such as the COVID-19 pandemic. Enhancing social capital, institutionalization, and developing required infrastructures by the government will improve public–private partnerships.

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Section: Discussionmentioning

confidence: 99%

Public-Private-People Partnerships (4P) for Improving the Response to COVID-19 in Iran

Seddighi

Salmani

et al. 2020

Disaster med. public health prep.

View full text Add to dashboard Cite

show abstract

“…Type of fixed-line package, the monthly subscription fee for fixed-line package, outside option ✔ ✘ [23] Used a combination of software and paper-based interviews to study customer preferences for prepaid mobile internet bundles. Deployed Bayesian D-optimal design procedure to design choice sets from four main attributes.…”

Section: Summary Of Studiesmentioning

confidence: 99%

Comparing Two Deep-Learning Models in Discrete Choice Analysis of Customers’ Mobile Plan Preferences

Oliobi,

Chinhamu,

Zewotir

2024

Applied Sciences

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A discrete choice experiment (DCE) was used to investigate students’ preferences for mobile phone plans at a South African university. Upon obtaining the data, this study compares the predictive performance of two machine-learning models for discrete choice analysis and makes recommendations for model selection. Using concepts from blocked fractional factorial designs, a locally optimal DCE was created for the choice sets. This contrasts with alternative ways that, in practice, could be more difficult, especially when there is a large number of attributes. The call rate, data speed, customer service, premiums, and network coverage were the features considered. A total of 180 respondents were chosen from the student population using a two-stage sample approach, and data were gathered through face-to-face interviews. In this study, two deep-learning models are examined to analyze the data, which are the artificial neural network (ANN) and the extreme gradient boosting (XGBoost) models. Root mean square error (RMSE) and mean absolute error (MAE) are used to assess the model fitness, while accuracy, precision, recall and F1 score were used to compare the models’ performance. The results showed that XGBoost performs better compared to ANN in model fitness and prediction. Thus, the use of the XGBoost deep-learning model in choice preference modeling is therefore encouraged.

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Offering the right incentive at the right time: Leveraging customer mental accounting to promote prepaid service

Qiu

Yang

et al. 2022

Annals of Tourism Research

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Analysis of consumer preferences for prepaid mobile internet packages in Iran: A Discrete Choice Experiment

Cited by 3 publications

References 0 publications

Public-Private-People Partnerships (4P) for Improving the Response to COVID-19 in Iran

Public-Private-People Partnerships (4P) for Improving the Response to COVID-19 in Iran

Comparing Two Deep-Learning Models in Discrete Choice Analysis of Customers’ Mobile Plan Preferences

Offering the right incentive at the right time: Leveraging customer mental accounting to promote prepaid service

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