Does Online Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

User-Generated Content in online platforms or chatter for short provides a valuable source of consumer feedback on market performance of firms. This study examines whether chatter can predict stock market performance, which metric of chatter has the strongest relationship, and what the dynamics of the relationship are. The authors aggregate chatter (in the form of product reviews) from multiple websites over a four year period across six markets and fifteen firms. They derive multiple metrics of chatter (volume, positive chatter, negative chatter, and 5-start ratings) and use multivariate time series models to assess the short and long term relationship between chatter and stock market performance. They use three measures of stock market performance: abnormal returns, risk, and trading volume. The findings reveal that two metrics of chatter can predict abnormal returns with a lead of a few days. Of four metrics of chatter, volume shows the strongest relationship with returns and trading volume, followed by negative chatter. Whereas negative chatter has a strong effect on returns and trading volume with a short “wearin” and long “wearout,” positive chatter has no effect on these metrics. Negative chatter also increases volatility (risk) in returns. A portfolio analysis of trading stocks based on their chatter provides a return of 8% over and above normal market returns. In addition to the investing opportunities, the results show managers that chatter is an important metric to follow to gauge the performance of their brands and products. Because chatter is available daily and hourly, it 2 can provide an immediate pulse of performance that is not possible with infrequent sales and earnings reports. The fact that negative chatter is more important than positive, indicates that negatives are more diagnostic than positives. The negatives suggest what aspects of the products managers should focus on

Big data marketing during the period 2012–2019: a bibliometric review

The present study identifies the most significant trends in production of high impact scientific papers related to the Big Data Marketing variable during the period between the years 2012 and 2019 through a revision of the Scopus database, which manages to highlight the relevance of 113 indexed papers. For this purpose, the following descriptive bibliometric indicators are implemented: production volume, type of document, number of citations, and country of application. In the studied time period, the evidence suggests an annual growth in the production volume of papers related to the variable, but with a significant drop in 2017. The knowledge areas that showcases more researches about the Big Data Marketing variable are computer science, mathematics, decision-making, and engineering domain

PERENCANAAN FDD-LTE MENGGUNAKAN FREKUENSI 1800MHZ PADA PERANCANGAN INDOOR BUILDING COVERAGE DI YOGYA KEPATIHAN BANDUNG

Material sebuah gedung merupakan salah satu penyebab dari terjadinya fading sehingga menghambat sinyal masuk ke dalam gedung yang mengakibatkan sinyal didalam gedung tersebut lemah. Pada gedung Yogya Kepatihan memiliki masalah terhadap kualitas jaringan didalamnya sehingga butuh dilakukannya perencanaan Indoor untuk mengatasi masalah tersebut. Berdasarkan hasil analisis dilakukannya walk test diperoleh nilai rata-rata dari RSRP sebesar -96 dBm dan SINR sebesar 8 dB, sedangkan drivetest sekitaran Gedung memperoleh hasil RSRP sebesar -72 dBm dan SINR sebesar 5 dB. Penerapan Indoor Building Coverage (IBC) ini menggunakan sistem Distributed Antenna System (DAS) dengan teknik FDD-LTE pita frekuensi 1800 MHz, untuk simulasinya menggunakan Radiowave Propagation Software (RPS) dengan model propagasi Cost-231 Multi-Wall Indoor. Operator Telkomsel menjadi kasus dalam penerapan ini. Walktest di dalam gedung menggunakan Nemo handy, sedangkan drivetest menggunakan GnetTrack Pro. Setelah mendapatkan data lalu dilanjutkan perhitungan capacity planning dan coverage planning sehingga mendapatkan perhitungan untuk jumlah antena yang akan di simulasikan ke dalam software RPS untuk mendapatkan hasil parameter yang sesuai dengan standar Key Performance Indicator (KPI) Operator Telkomsel yaitu RSRP > -85 dBm dan SINR > 10 dB. Dari hasil simulasi ini, diperoleh peningkatan nilai rata-rata RSRP > -76 dBm sebanyak 81,95% dan rata-rata nilai SINR > 26 sebanyak 71,56%. Kata Kunci: LTE, FDD, IBC, DAS, RPS

Customer Experience Management

Dieser Beitrag leistet einen Beitrag zur Marketingforschung, da er den jungen aber von zunehmender Relevanz geprägten Forschungsstrang zum Themenkomplex CEM grundlegend entwickelt. Zum einen zeigt das identifizierte Rahmenkonzept auf, dass CEM über einzelne unternehmerische Fähigkeiten wie dem Design von Serviceerlebnissen, das die bisherige CEM-Forschung bestimmt hat, hinausgeht. Zum anderen leistet das Konzept einen Beitrag zur Synthese fragmentierter, aber miteinander zusammenhängender Literaturströmungen in der Marketingforschung ..

Do Social Media Investments Pay Off? Preliminary evidence from Swiss destination marketing organizations

ocial media has become a dominant subject in tourism and hospitality research. Given the importance of social media in the customer journey, destination marketing organizations (DMOs) need to understand the effectiveness of their social media activities. This paper analyses the relationship between DMOs’ marketing spending and staffing and various social media key performance indicators (KPIs). We used an online questionnaire to collect data about social media activities and respective marketing budgets of DMOs in Switzerland for the reference year 2014. We also gathered social media KPI figures of the five main social media platforms used by these DMOs (i.e. Facebook, Twitter, Google+, YouTube, and Instagram). Our results suggest that DMOs’ investments in social media (allocated resources for marketing, online marketing, and especially social media) correlate with identified metrics for measuring social media success

Weight Analysis of the Factors Affecting eWOM Providing Behavior

noElectronic word of mouth (eWOM) significantly affects the consumer decision-making process. A number of studies investigated why consumers provide eWOM communications. Existing literature has contradicting factors regarding factors affect eWOM providing behaviour. This study aims to evaluate factors affecting eWOM providing behaviour by performing a systematic review and weight analysis of existing research outputs. Based on the result of weight analysis it was found that the best predictors of eWOM providing behaviour are involvement, self-enhancement, and trust in web eWOM services. Scholars can use the results of this study when making decisions regarding the inclusion of factors in their research. Practitioners can pay more attention to the best predictors