The recent surge in the usage of social media has created an enormous amount of user‐generated content (UGC). While there are streams of research that seek to mine UGC, these research studies seldom ...tackle analysis of this textual content from a quality management perspective. In this study, we synthesize existing research studies on text mining and propose an integrated text analytic framework for product defect discovery. The framework effectively leverages rich social media content and quantifies the text using various automatically extracted signal cues. These extracted signal cues can then be used as modeling inputs for product defect discovery. We showcase the usefulness of the framework by performing product defect discovery using UGC in both the automotive and the consumer electronics domains. We use principal component analysis and logistic regression to produce a multivariate explanatory analysis relating defects to quantitative measures derived from text. For our samples, we find that a selection of distinctive terms, product features, and semantic factors are strong indicators of defects, whereas stylistic, social, and sentiment features are not. For high sales volume products, we demonstrate that significant corporate value is derivable from a reduction in defect discovery time and consequently defective product units in circulation.
In recent years, social networking systems have become quite popular, and have been established for a variety of purposes. However, it is still not well understood if sense of community (SOC) ...contributes to an individual user's continued usage of these systems. This paper presents a theoretical model combining key constructs from the SOC framework and the information systems usage/success models to evaluate social networking usage. We surveyed users from popular social networking sites to test the validity of the research model. Our results indicate that while user satisfaction is still the most salient determinant for system usage, SOC also plays a significant role in the user's online social interaction process. Besides its direct influence on usage, SOC also indirectly influences usage through user satisfaction. In addition, we show that SOC is a multidimensional construct that should be measured using several components. We also demonstrate that the quality of the information contained in the communities has a significant impact on SOC, but system quality does not seem to influence it. Theoretical and practical implications of the study are discussed.
With increasing knowledge demands and limited availability of expertise and resources within organizations, professionals often rely on external sources when seeking knowledge. Online knowledge ...communities are Internet based virtual communities that specialize in knowledge seeking and sharing. They provide a virtual media environment where individuals with common interests seek and share knowledge across time and space. A large online community may have millions of participants who have accrued a large knowledge repository with millions of text documents. However, due to the low information quality of user-generated content, it is very challenging to develop an effective knowledge management system for facilitating knowledge seeking and sharing in online communities. Knowledge management literature suggests that effective knowledge management should make accessible not only written knowledge but also experts who are a source of information and can perform a given organizational or social function. Existing expert finding systems evaluate one's expertise based on either the contents of authored documents or one's social status within his or her knowledge community. However, very few studies consider both indicators collectively. In addition, very few studies focus on virtual communities where information quality is often poorer than that in organizational knowledge repositories. In this study we propose a novel expert finding algorithm, ExpertRank, that evaluates expertise based on both document-based relevance and one's authority in his or her knowledge community. We modify the PageRank algorithm to evaluate one's authority so that it reduces the effect of certain biasing communication behavior in online communities. We explore three different expert ranking strategies that combine document-based relevance and authority: linear combination, cascade ranking, and multiplication scaling. We evaluate ExpertRank using a popular online knowledge community. Experiments show that the proposed algorithm achieves the best performance when both document-based relevance and authority are considered.
► We propose ExpertRank, an expert finding technique in online knowledge communities. ► It evaluates experts on both knowledge relevance and authority in the community. ► PageRank is modified to reduce the bias of small-interconnected groups. ► ExpertRank outperforms both document-centric and hybrid expert finding techniques.
► We model a problem where jobs arrive in batches and need to be assigned to servers. ► When traffic is below a certain threshold, it is better to not assign any jobs to slower servers. ► The ...explicit formula for calculating the threshold is presented. ► The threshold-type routing policy extends to queueing systems with batch arrivals.
We revisit the problem of job assignment to multiple heterogeneous servers in parallel. The system under consideration, however, has a few unique features. Specifically, repair jobs arrive to the queueing system in
batches according to a Poisson process. In addition, servers are heterogeneous and the service time distributions of the individual servers are
general. The objective is to optimally assign each job within a batch arrival to minimize the long-run average number of jobs in the entire system. We focus on the class of static assignment policies where jobs are routed to servers upon arrival according to pre-determined probabilities. We solve the model analytically and derive the structural properties of the optimal static assignment. We show that when the traffic is below a certain threshold, it is better to
not assign any jobs to slower servers. As traffic increases (either due to an increase in job arrival rate or batch size), more slower servers will be utilized. We give an explicit formula for computing the threshold. Finally we compare and evaluate the performance of the static assignment policy to two dynamic policies, specifically the shortest expected completion policy and the shortest queue policy.
Monoclinic and hexagonal LaPO4:5 mol.%Eu3+ phosphors were synthesized with merely adjusting pH values of solutions by a hydrothermal method at the same synthesis temperature. The microstructure, ...morphology and photoluminescence of Eu3+-doped LaPO4, which were influenced by different preparation conditions, were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy and luminescence spectroscopy, respectively. The specimen showed monoclinic structure in strong acid solution, however, it changed into hexagonal structure in weak acid solution and strong alkali solution. The monoclinic LaPO4:Eu3+ showed the longest length to diameter ratio, which was attributed to the preferential growth of -112. The monoclinic specimen exhibited a slight red shift in infrared spectra, Raman band positions and charge transfer (CT) compared with hexagonal specimens. Moreover, the calculated results of grain sizes, lattice parameters, full width at half maximum in Raman patterns and emission integral intensity were in good agreement with analysis results. The monoclinic specimen showed the maximal absolute luminescence quantum yield (0.4) and the second lifetime τ2 (0.52 ms), which was accordant with red-orange emission in CIE. The 5D0→7F1 occupied a dominate position in hexagonal specimens, which indicated that more Eu3+ in the hexagonal structure were occupied inversion center of symmetry sites.
SEM images of products obtained at pH=12, 900 °C
Using longitudinal data of IT professionals’ activities in the SAP Community Network, and the career histories of these professionals obtained from LinkedIn, we investigate the relationship between ...an individual’s participation in Internet-enabled open knowledge communities and a major event of his/her career development: jobhopping. We measure individual participation in open knowledge communities by two dimensions of related activities: contribution and learning. We provide empirical evidence that contribution to knowledge communities leads to a higher likelihood of job-hopping, yet a greater amount of learning is associated with a higher probability of retention. We argue that the effect of contribution can be attributed to job market signaling and the effect of learning is primarily driven by enhanced job performance and career advancement within the current organization. A series of robustness tests were conducted to address the self-selection bias and to rule out some possible alternative explanations to these mechanisms. Our work contributes to the existing body of literature on networks of practice and provides supporting evidence that participation in these networks indeed leads to career benefits and status advancements. Additionally, our study takes the first step to fill the gap in the current literature on voluntary employee turnover that has so far ignored the impacts of employee participation in external knowledge communities, thus providing both theoretical and practical insights in the area of organizational research.
Over the last few years, the Web-based services, more specifically different types of E-Commerce applications, have become quite popular, resulting in exponential growth in the Web traffic. In many ...situations, this has led to unacceptable response times and unavailability of services, thereby driving away customers. Many companies are trying to address this problem using multiple Web servers with a front-end load balancer. Load balancing has been found to provide an effective and scalable way of managing the ever-increasing Web traffic. However, there has been little attempt to analyze the performance characteristics of a system that uses a load balancer. This paper presents a queuing model for analyzing load balancing with two Web servers. We first analyze the centralized load balancing model, derive the average response time and the rejection rate, and compare three different routing policies at the load balancer. We then extend our analysis to the distributed load balancing and find the optimal routing policy that minimizes the average response time.
Corporate fraud can lead to significant financial losses and cause immeasurable damage to investor confidence and the overall economy. Detection of such frauds is a time-consuming and challenging ...task. Traditionally, researchers have been relying on financial data and/or textual content from financial statements to detect corporate fraud. Guided by systemic functional linguistics (SFL) theory, we propose an analytic framework that taps into unstructured data from financial social media platforms to assess the risk of corporate fraud. We assemble a unique data set including 64 fraudulent firms and a matched sample of 64 nonfraudulent firms, as well as the social media data prior to the firm's alleged fraud violation in Accounting and Auditing Enforcement Releases (AAERs). Our framework automatically extracts signals such as sentiment features, emotion features, topic features, lexical features, and social network features, which are then fed into machine learning classifiers for fraud detection. We evaluate and compare the performance of our algorithm against baseline approaches using only financial ratios and language-based features respectively. We further validate the robustness of our algorithm by detecting leaked information and rumors, testing the algorithm on a new data set, and conducting an applicability check. Our results demonstrate the value of financial social media data and serve as a proof of concept of using such data to complement traditional fraud detection methods.
•Structural, electronic and optical properties of LaPO4:Eu are investigated.•Eu doping introduces impurity energy levels to make band gap decreased.•O(2p)–Eu(4f) charge transfer energy is ...calculated.•We assign the optical transitions according to calculated results.•The occupation of Eu3+ in LaPO4 synthesized in this work is determined.
Monoclinic LaPO4 and LaPO4:Eu have been prepared by the hydrothermal method. The phase composition, UV–Vis absorption spectrum, excitation and emission spectra of as-obtained products were measured. Theoretical calculations of the structural, electronic and optical properties of LaPO4 and LaPO4:Eu were also carried out. The results indicated that the lattice parameters, energy gap and optical properties were in good agreement with the experimental results. The impurity energy levels induced by the 4f states of Eu expanded the absorption edge and decreased the band gap. The charge transfer energy of O(2p)–Eu(4f) calculated was about 4.41eV, which was close to the value achieved in excitation spectrum (4.5eV).
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 is generally believed that ...the existence of such unauthorized sales will cannibalize the profits of brand owners. In this paper, we develop a pricing model for a firm that sells an identical product in two distinct markets but faces the threat of potential gray market sales. The firm chooses prices in each market. A consumer chooses whether to buy the product from one of the markets including a gray market. We derive the optimal prices in the two markets and examine their effects on consumer demand and the total profit. We show that the higher price in one market transfers part of its demand into the gray market, thus influencing the consumer demand in the low-priced market as well. Additionally, the price gap between the two separate markets positively influences gray market sales and, under certain conditions, can lead to an increase in firm profit. Using authorized sales data from a Fortune 100 company and a separate data set on online gray market sales, we find empirical evidence in support of our model results.
