1. Does data analytics use improve firm decision making quality? The role of knowledge sharing and data analytics competency

    Using data analytics significantly improves knowledge sharing within firms. Knowledge sharing fully mediates data analytics usage impact on decision quality. Knowledge sharing does not necessarily improve firm decision quality. Data analytics competency moderates knowledge sharing impact on decision quality.

  2. Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms

    we build a prediction model of movie box office revenue by empirically exploring its intricate relationships with user-generated content (UGC) as well as marketer-generated content (MGC) on a microblogging platform and UGC on a third-party platform. Our analyses are based on a panel vector autoregression (PVAR) model that is calibrated with a combination of data from Weibo (microblogging platform) and Douban! Movies (third party). Our empirical results show that microblogging UGC (MUGC) is a significant predictor of box office revenue and has stronger predictive power than UGC on Douban! Movies (DUGC).

  3. Seizing the Commuting Moment: Contextual Targeting Based on Mobile Transportation Apps

    Despite the average daily commuting time of commuters increasing by the day, the way marketers can benefit from our commuting behaviors has not yet been examined. In collaboration with one of the largest global mobile telecom providers, this study investigates how contextual targeting with commuting impacts user redemptions of mobile coupons. The analysis is based on a rich field study in which 14,741 mobile coupons were sent to 9,928 public transit app users consisting of commuters and noncommuters. The key findings indicate that commuters are about 3× as likely to redeem their mobile coupon compared with noncommuters. However, a multiple-coupon distribution strategy is more effective in increasing redemption among noncommuters than commuters. Moreover, the redemption rate of commuters is higher for coupons with shorter expiration periods, whereas that of noncommuters is higher for coupons with longer expiration periods. On the basis of theories from psychology and physiology, we argue that stress, which is exacerbated by commuting, increases commuters’ coupon redemption rate. We provide empirical support for this argument and show that marketers can increase response rates by focusing on specific periods of the day when commuting stress is relatively high (e.g., rush hours). By carefully exploiting commuting, which is easily identifiable and occurs throughout the world, managers may improve their mobile marketing effectiveness.

  4. The Digital Sin City: An Empirical Study of Craigslist’s Impact on Prostitution Trends

  5. Is the value of travel time savings increasing? Analysis throughout a financial crisis

  6. Exploring effects of environment density on heterogeneous populations’ level of service perceptions

  7. Do Electronic Health Records Affect Quality of Care? Evidence from the HITECH Act

    In contrast to existing research that has focused on EHR investments or adoption, we propose that its actual use should be the focus in evaluating the advantages of EHRs. We leveraged the meaningful use (MU) provisions of the HITECH Act to quantify different degrees of EHR use in a large and heterogeneous set of hospitals. The results provided evidence of EHRs’ positive effects on quality of care and reconciled earlier mixed findings by showing that their benefits vary according to different levels of use and hospital characteristics.

  8. Transit Pattern Detection Using Tensor Factorization

    In this paper, we propose a framework based on transit tensor factorization (TTF) to identify citywide travel patterns. In particular, we create a transit tensor, which summarizes the citywide OTD information of all passenger trips captured in the AFC records. The TTF framework imposes spatial regularization in the formulation to group nearby stations into meaningful regions and uses multitask learning to identify traffic flows among these regions at different times of the day and days of the week. Evaluated with large-scale, real-world data, our results show that the proposed TTF framework can effectively identify meaningful citywide transit patterns.

  9. Stochastic Network Design for Planning Scheduled Transportation Services: The Value of Deterministic Solutions

    We study several problem variants and models and investigate, for each case, the immediate quality of the deterministic solutions stemming from the 50th and the 75th percentile of the demand distributions. We then show that for all models, but in different ways, we are able to make effective use of parts of the deterministic solution, confirming the value of the deterministic solution in the stochastic environment, even when the deterministic solution itself performs badly.

  10. Optimal Market Entry Timing for Successive Generations of Technological Innovations

  11. The Experts in the Crowd: The Role of Experienced Investors in a Crowdfunding Market

  12. What Users Do Besides Problem-Focused Coping in the IT Security Context: An Emotion-Focused Coping Perspective

  13. Process Analytics Approach for R&D Project Selection

    Motivation: billions of dollars R&D project selection Research gaps: not effective; ignore insight: quality of the reviewers, social relationships Proposed method: data-driven decision models; NSFC