Understanding users' switching behavior of mobile instant messaging applications: An empirical study from the perspective of push-pull-mooring framework
“…Mobile instant messaging (MIM) apps are becoming highly popular in recent years, as a technological (and free, in some cases) evolution of short messages (namely, SMS) [11][12][13], providing a mean to enhance social interrelationships [12]. According to a research performed in late 2013 [14], only in China there were about 1.48 billion accounts in instant messaging (IM) services.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, creating an IM app and getting people to use it is not a complicated process. What it is a difficult task is to keep users to continue using the service because the cost of switching between applications is very low [13,30]. erefore, this is why it is so vital to evaluate and improve the usability of this type of apps.…”
With the rise of mobile devices and the high number of instant messaging applications available in the stores, it is necessary to evaluate the usability of such applications to provide a more satisfying user experience. To this end, this paper presents a methodical usability evaluation of instant messaging applications both in iOS and Android platforms. A predefined evaluation was used, which was created to detect the main usability issues of mobile applications, regardless of the device used and the evaluated applications. Consequently, two methods were used: the keystroke level model and the mobile heuristic evaluation. Also, the results suggest that the main problems of this type of applications are difficulties in performing tasks (some of them were not agile nor easy to complete), lack of element cohesion (some icons and buttons did not follow the style of the operating system, bad translations, and too much information on the screen), problems with the user interface (pop-ups overlapping the status bar, clipped elements, sometimes the interface did not rotate, and, in other cases, the interface changed considerably when the device was rotated), and lack of information about privacy and security features. Finally, based on the results, we propose a set of recommendations that will be helpful for developers of this kind of applications.
“…Mobile instant messaging (MIM) apps are becoming highly popular in recent years, as a technological (and free, in some cases) evolution of short messages (namely, SMS) [11][12][13], providing a mean to enhance social interrelationships [12]. According to a research performed in late 2013 [14], only in China there were about 1.48 billion accounts in instant messaging (IM) services.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, creating an IM app and getting people to use it is not a complicated process. What it is a difficult task is to keep users to continue using the service because the cost of switching between applications is very low [13,30]. erefore, this is why it is so vital to evaluate and improve the usability of this type of apps.…”
With the rise of mobile devices and the high number of instant messaging applications available in the stores, it is necessary to evaluate the usability of such applications to provide a more satisfying user experience. To this end, this paper presents a methodical usability evaluation of instant messaging applications both in iOS and Android platforms. A predefined evaluation was used, which was created to detect the main usability issues of mobile applications, regardless of the device used and the evaluated applications. Consequently, two methods were used: the keystroke level model and the mobile heuristic evaluation. Also, the results suggest that the main problems of this type of applications are difficulties in performing tasks (some of them were not agile nor easy to complete), lack of element cohesion (some icons and buttons did not follow the style of the operating system, bad translations, and too much information on the screen), problems with the user interface (pop-ups overlapping the status bar, clipped elements, sometimes the interface did not rotate, and, in other cases, the interface changed considerably when the device was rotated), and lack of information about privacy and security features. Finally, based on the results, we propose a set of recommendations that will be helpful for developers of this kind of applications.
“…Gerrard dan Cunningham (2000) mengembangkan metode pembobotan sederhana yang diterapkan pada berbagai insiden switching yang mereka ciptakan. Namun, sampai saat ini, tidak ada yang meminta pengalih perhatian untuk memberi bobot pada berbagai insiden yang menyebabkan mereka beralih, Perilaku berpindah pelanggan telah dipelajari di berbagai bidang seperti layanan perbankan, seperti penelitian yang dilakukan oleh (Michael D. Clemes, 2010), service provider (Yongqiang Sun & c, 2017), perpindahan merek (Arvind Sahay and Nivedita Sharma), belanja online, hi-tech produk (Zeeshan Ahmed 2015), pemilihan maskapai penerbangan (Jishim Jung, 2017), situs jejaring sosial (Chun-Nan Lin, 2017), dll. (Sanjukta Pookulangara, 2011, meneliti perilaku berpindah konsumen dengan menggunakan Theory of Planned Behavior (TPB).…”
AbstrakPerilaku perpindahan pelanggan terjadi saat pelanggan meninggalkan layanan atau produk awal yang mereka gunakan dan menggantinya dengan produk atau layanan baru. Fenomena ini menarik untuk diteliti seiring dengan ketatnya persaingan dan perkembangan teknologi yang memunculkan banyak alternatif produk dan layanan untuk dipilih oleh konsumen. Penelitian ini bertujuan untuk menganalisis perkembangan riset di bidang perilaku perpindahan layanan yang dilakukan oleh konsumen. Metode yang dipergunakan adalah literatur review, yaitu dengan menganalisis jurnal yang terbit pada tahun 2010 sampai dengan 2017 pada publisher emerald dan elsevier. Keyword yang dipergunakan untuk mencari adalah "consumer switching behavior". Hasil studi pada 13 artikel jurnal ditemukan bahwa variabel yang dipergunakan untuk menganalisis perilaku perpindahan layanan di ambil dari beberapa teori perilaku yang sudah banyak dipergunakan, seperti Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), dan Technology Acceptance Model (TAM). Sedangkan beberapa penelitian terbaru menunjukkan bahwa teori push and pull mooring dirasakan lebih tepat dipergunakan untuk mengukur dan menganalisis perilaku perpindahan layanan "switching behavior". Yaitu dengan memasukkan faktor pendorong (push factors), faktor penarik (pull factors) dan faktor yang menjadi penghambat perpindahan (mooring factors).
Kata Kunci : TRA, TPB, TAM, Push Factor, Pull Factor, Mooring Factor
PendahuluanJumlah pengguna media online secara global menunjukkan angka sekitar 1,3 miliar pada akhir tahun 2007. Proyeksi menunjukkan bahwa angka tersebut akan mencapai 1,8 miliar pada tahun 2010 dan akan semakin tinggi di tahun 2017. Akses internet dunia berkembang begitu pesat sehingga orang sekarang online hampir setiap hari untuk melakukan segala sesuatu mulai dari pengecekan pernyataan bank mereka, untuk berbelanja, untuk mencari informasi atau hanya sekedar mencari hiburan dan bermain game. Pemanfaatan teknologi informasi di Indonesia dalam mendukung aktifitas masyarakat mengalami pertumbuhan yang sangat pesat, seiring dengan pertumbuhan jumlah pengguna smartphone dan media internet yang angkanya mencapai 83,7 juta orang pada 2014 (https://www.kominfo.go.id, 2014). Tahun 2016 pengguna internet di indonesia meningkat menjadi 132,7 juta orang diperkirakan akan terus mengalami kenaikkan di tahun 2017 (Internetworldstats.com, 2016). Jumlah tersebut mendudukkan Indonesia di peringkat ke-6 terbesar di dunia dalam hal jumlah pengguna internet. Perkembangan dalam bidang teknologi informasi berdampak pada iklim bisnis yang menjadi semakin kompetetif. Sebagai konsekuensinya volume kegiatan ekonomi digital menjadi semakin masif. Interaksi individu lintas negara dalam kaitannya dengan kegiatan perdagangan dan bisnis menjadi semakin cepat.
“…For example, the Apple App Store reveals an increase in the number of available apps, from 1,200,000 (as of July 2014) to 2,200,000 (as of January 2017) [5,6]. Among all those applications there are some for written communication that have become ubiquitous in contemporary society [7,8], such as instant messaging (so called IM apps), social networks, or email apps.…”
Section: Introductionmentioning
confidence: 99%
“…IM apps are the newest and most popular evolution of near-synchronous text technologies [9][10][11]; thus, they are used to facilitate social relationships [12] and are one of the most widely used apps, since this type of app has become an alternative (usually free or cheaper) to the traditional SMS messages [8,10,13]. Since there are so many apps for the same purpose in the mobile markets, users have too many alternatives to choose and therefore they are quite critical about how an app works.…”
Nowadays, instant messaging applications (apps) are one of the most popular applications for mobile devices with millions of active users. However, mobile devices present hardware and software characteristics and limitations compared with personal computers. Hence, to address the usability issues of mobile apps, a specific methodology must be conducted. This paper shows the findings from a systematic analysis of these applications on iOS mobile platform that was conducted to identify some usability issues in mobile applications for instant messaging. The overall process includes a Keystroke-Level Modeling and a Mobile Heuristic Evaluation. In the same trend, we propose a set of guidelines for improving the usability of these apps. Based on our findings, this analysis will help in the future to create more effective mobile applications for instant messaging.
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