Sifting through vast collections of unstructured or semistructured data beyond the reach mining tools, text tracks information sources, links isolated concepts in distant documents, maps relationships between activities, and helps answer questions.

The recent surge in the usage of social media has created an enormous amount user‐generated content (UGC). While there are streams research that seek to mine UGC, these studies seldom tackle analysis this textual from a quality management perspective. In study, we synthesize existing on text mining and propose integrated analytic framework for product defect discovery. effectively leverages rich quantifies using various automatically extracted signal cues. These cues can then be used as...

Corporate fraud can lead to significant financial losses and cause immeasurable damage investor confidence the overall economy. Detection of such frauds is a time-consuming challenging task. Traditionally, researchers have been relying on data and/or textual content from statements detect corporate fraud. Guided by systemic functional linguistics (SFL) theory, we propose an analytic framework that taps into unstructured social media platforms assess risk We assemble unique set including 64...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In recent years, social networking systems have become quite popular, and been established for a variety of purposes. However, it is still not well understood if sense community (SOC) contributes to an individual user's continued usage these systems. This paper presents theoretical model combining key constructs from the SOC framework information usage/success models evaluate usage. We surveyed...

In today's dynamic business environment, companies are under tremendous pressure to become more innovative and maintain a steady stream of ideas that can lead new improved products services. Companies have begun explore the possibility capturing consumers' "collective intelligence" by establishing firm-sponsored online brainstorming sites where individuals share their offer comments on contributed others. We term these "Company-Sponsored Online Co-Creation Brainstorming" (COCB). The value...

On-demand ride-sharing, as one of the most representative sectors sharing economy has received a lot attention and significant debate. Limited conclusive empirical research been done to investigate social welfare such service. In this research, we conduct difference-in-difference analysis examine impact Uber, an on-demand app-based ride service, on urban traffic congestion. We find that after Uber entry, congestion area reduced significantly. order check robustness results, instrumental...

In this study, we utilize a kernel theory of knowledge adoption model and propose novel text analytic framework to classify the usefulness solutions in online communities. The study combines multiple disciplines (behavioral, empirical, design science, technical) tackle an important relevant business problem: how effectively manage repository identify useful solutions. Our can be implemented communities improve users’ experience searching for knowledge. proposed has potential guide...

The role of information technology (IT) in managing operations that support environmentally sustainable growth has been emphasized a lot management and systems research. In this paper, we study the impact IT‐based on‐demand ridesharing platforms on an important aspect sustainability—traffic congestion. Our theoretical prediction suggests two countervailing effects from entry to urban areas: efficiency‐enhancing effect reduces traffic congestion demand‐inducing increases We propose impacts...

The sharing economy has fundamentally changed the way many individuals work. In this paper, we study impact of entry a major ridesharing platform into U.S. Metropolitan Statistical Areas (MSAs), on supply and demand sides labor market. Leveraging difference-in-differences (DID) research design data set combining multiple Census archival sources, exploit variation in market metrics before after Uber’s MSAs. Our empirical findings reveal that introduction an empowering effect workers (the side...

Unstructured multimedia data (text and audio) provides unprecedented opportunities to derive actionable decision-making in the financial industry, areas such as portfolio risk management. However, due formidable methodological challenges, promise of business value from unstructured has not materialized. In this study, we use a design science approach develop DeepVoice, novel nonverbal predictive analysis system for prediction, setting quarterly earnings conference calls. DeepVoice forecasts...

The role of information technology (IT) in managing operations that support environmentally sustainable growth has been emphasized a lot management and systems research. In this paper, we study the impact IT-based on-demand ridesharing platforms on an important aspect sustainability – traffic congestion. Our theoretical prediction suggests two countervailing effects from entry to urban areas: efficiency-enhancing effect reduces congestion demand-inducing increases We propose impacts services...

Using longitudinal data of IT professionals’ activities in the SAP Community Network, and career histories these professionals obtained from LinkedIn, we investigate relationship between an individual’s participation Internet-enabled open kn

Maliciously false information (disinformation) can influence people's beliefs and behaviors with significant social economic implications. In this study, we examine news articles on crowd‐sourced digital platforms for financial markets. Assembling a unique dataset of that were investigated prosecuted by the Securities Exchange Commission, along propagation data such performance focal firm, develop well‐justified machine learning system to detect disinformation published media platforms. Our...

The sale of genuinely branded products through unauthorized channels (also known as gray markets) is a growing problem for many firms that operate in separate markets. It generally believed the existence such sales will cannibalize profits brand owners. In this paper, we develop pricing model firm sells an identical product two distinct markets but faces threat potential market sales. chooses prices each market. A consumer whether to buy from one including We derive optimal and examine their...

Web-based knowledge communities (WKCs) allow individuals with similar interests to collectively engage in acquisition and exchange. In spite of increased research interest the topic online exchange social interaction, few studies have identified factors that contribute WKC success. this study we apply Preece's community success framework usability sociability information system (IS) model as conceptual foundations for an investigation into lead We present empirically test a using survey data...

To cut costs, companies have chosen to deliver a variety of service offerings online. However, the digital systems providing such services (e-service) always been complemented with or supported by human-based (h-service). Whereas h-service has total costs that increase demand for services, e-service mainly requires fixed investment upfront, which can be amortized over totality customers served. Considering different nature and heterogeneity customer preferences we derive optimal mix...

The global economic disruption brought by COVID‐19 crisis can set a stage for the prevalence of financial statement frauds, which jeopardize efficient functioning capital markets. In this paper, we propose nuanced method to detect frauds tracking granular changes in disclosures over time. Specifically, first align paragraphs between consecutive their similarities. This alignment be solved as an optimization‐based matching problem. Then identify three types changed contents: recurrent, newly...

Despite much hype about electronic payments systems (EPSs), a 2004 survey establishes that close to 80% of between-business are still made using paper-based formats. We present finite mixture logit model predict likelihood EPS adoption in business-to-business (B2B) settings. Our simultaneously classifies firms into homogeneous segments based on firm-specific characteristics and estimates the model's coefficients relating predictor variables decisions for each respective segment. While such...

Abstract In the work presented here, we develop and apply preference markets in evaluating early stage technology. Partnering with a Fortune 5 company, developed implemented two internal (field experiments). both cases, nonmonetary (play money) incentives were utilized, but one market provided additional incentives. Working partner our investigation started seven emerging technologies expanded to total of 17 technologies. Our results suggest that even simple form play money incentive yielded...