The quality of user experiences for mobile recommendation systems: an end-user perspective

Chong, Woon Kian; Ma, Zhuang

doi:10.1108/imds-07-2020-0389

Cited by 5 publications

(3 citation statements)

References 64 publications

(93 reference statements)

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“…Smart push means that the contents can be sent to the app users automatically based on their previous or inputted preferences by using a series of data-driven algorithm (Lacey, 2014). Essentially, the logic of smart push is a push-based communication model, which is currently the most popular paradigm for building smartphone apps with the rising of wireless and cellular networks (Chong & Ma, 2021; Sofia & Mendes, 2019). Hsu and Tang (2020) argued that smart push is one of the key features of current smartphone apps.…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

The dark side of smartphone application’s smart push function: Exploring its impact on fear of missing out and smartphone addiction

He,

Zeng

2024

Communication and the Public

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This article aims to investigate the negative effects of smart push technology, which is becoming increasingly popular in digital devices and online services, particularly in smartphone-based applications (apps). Specifically, empirical relationships among the features of the app content delivered by smart push technology, fear of missing out, and smartphone addiction are explored by constructing an integrated model. The proposed relationships were tested by analyzing survey-based data collected from 227 valid samples through partial least squares-structural equation modeling. The analysis confirmed the hypothesized positive relationships among the features of app content delivered by smart push technology (entertainment and timeliness) in smartphone-based apps, fear of missing out, and smartphone addiction. Moreover, fear of missing out served as a mediator between the features of smart push technology and smartphone addiction. This study makes a significant theoretical contribution to the digital communication technology and smartphone addiction literature by revealing the influence mechanism of smart push technology on smartphone addiction. Furthermore, this study has a number of practical implications for policymakers as well as app developers.

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Section: Literature Review and Hypothesesmentioning

confidence: 99%

The dark side of smartphone application’s smart push function: Exploring its impact on fear of missing out and smartphone addiction

He,

Zeng

2024

Communication and the Public

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“…Another complementary business resource, user involvement, has also been found to be positively related to EC adoption and implementation (Chong and Ma, 2021). In the context of EC, involving end-users, such as marketing personnel, in the early stage of EC development is imperative to developing a more user-friendly website, which in turn drives customer traffic and higher profitability.…”

Section: Complementary Business Resources and Ec Functionalitymentioning

confidence: 99%

Complementary resources and SME firm performance: the role of external readiness and E-commerce functionality

Yang

Xun

Chong³

2022

IMDS

Self Cite

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PurposeElectronic commerce (EC) strategy – performance logic has gained significant popularity in the literature, particularly from the resource-based view (RBV) of theoretical underpinning. However, such an obsession of focusing on organizations' complementary resources has been increasingly challenged, which has pressed the RBV to examine the possibility of external factors that can also impact firm performance. In this study, the authors shed light on the firm's external readiness—defined as the extent to which a firm's customers and suppliers perceive EC as important—in the relationship between SME's complementary resources and firm performance.Design/methodology/approach The authors employed a refined data set based on the British EC Award database, in which the authors sampled 430 British SMEs' senior managements and examined how EC investments made by the SMEs influenced firm performance, and how their external readiness moderated this main relationship.FindingsThe results showed that, in line with the RBV perspective, SMEs' complementary business resources and human resources both had strong and direct impacts on the firm performance. They were also strongly mediated by EC functionality. In addition, SMEs' external readiness moderated the relationship between human resources and firm performance and that of EC functionality on firm performance.Originality/value The findings contribute to RBV theory building by extending earlier research on the role of technology as performance enablers for SMEs and shed light on the often-overlooked role of SMEs' external readiness.

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“…Nowadays, recommendation systems are applied in many fields, including movie and commodity recommendation. In general, websites tend to provide recommendations based on the user's personal basic information, purchase history and browsing data such as ratings, to improve the perceived usefulness and system quality (Chong and Ma, 2021). For example, in collaborative filtering recommendation model (CF), users' ratings of products are taken into account for calculating the similarity between users or products, subsequently facilitating recommendations to users.…”

Section: Introductionmentioning

confidence: 99%

Is UGC sentiment helpful for recommendation? An application of sentiment-based recommendation model

Gao,

Wang,

Liu

2024

IMDS

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PurposeGiven the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.Design/methodology/approachAfter verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.FindingsThe results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.Practical implicationsThe findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.Originality/valueThis study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

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The quality of user experiences for mobile recommendation systems: an end-user perspective

Cited by 5 publications

References 64 publications

The dark side of smartphone application’s smart push function: Exploring its impact on fear of missing out and smartphone addiction

The dark side of smartphone application’s smart push function: Exploring its impact on fear of missing out and smartphone addiction

Complementary resources and SME firm performance: the role of external readiness and E-commerce functionality

Is UGC sentiment helpful for recommendation? An application of sentiment-based recommendation model

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