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Selective dissemination of information (SDI) is an information alerting service designed to keep individuals informed of new developments in their particular fields of interest. This investigation evaluated the use of SDI by basic research scientists working in a corporate environment. The following conceptual areas were considered in developing the best model of SDI use and productivity: 1, background of the individual; 2, work environment; 3, need to keep abreast of new research developments; 4, use of information sources; and 5, product‐ivity or number of papers published. One hundred and fifty‐six scientists met the entrance criteria and were analysed using both descriptive and inferential statistics. Multivariate models revealed several interesting patterns. Frequency of SDI use was found to be related to the work environment, need to keep abreast of new research developments, and use of primary and secondary information sources, including patents. Productivity was found to be related to background characteristics of the scientist, the work environment, need to keep abreast of new research developments and the use of a variety of information sources. Based on these research findings, scientists who use SDI on a regular basis appear to be more productive than their colleagues who are infrequent users, or who do not subscribe to the service.

Database marketers often select households for individual marketing contacts using information on past purchase behavior. One of the most common methods, known as RFM variables approach, ranks households according to three criteria: the recency of the latest purchase event, the long-run frequency of purchases, and the cumulative dollar expenditure. We argue that RFM variables approach is an indirect measure of the latent purchase propensity of the customer. In addition, the use of RFM information in targeting households creates major statistical problems (selection bias and RFM endogeneity) that complicate the calibration of forecasting models. Using a latent trait approach to capture a household's propensity to purchase a product, we construct a methodology that not only measures directly the latent propensity value of the customer, but also avoids the statistical limitations of the RFM variables approach. The result is a general household response forecasting and scoring approach that can be used on any database of customer transactions. We apply our methodology to a database from a charitable organization and show that the forecasting accuracy of the new methodology improves upon the traditional RFM variables approach.

Successful revenue management programs are found in industries where managers can accurately forecast customer demand. Airlines, rental car agencies, cruise lines, and hotels are all examples of industries that have been associated with revenue management. All of these industries have applied revenue management, whether it be complex overbooking models in the airline industry or simple price discrimination (i.e., having a tiered price system for those making reservations ahead of time versus walk-ups) for hotels.

This research examined the effect of information literacy (IL) on academic engagement (AE), cognitive engagement (CE) and academic performance among business students in Pakistan.

A cross-sectional survey was conducted to collect data from business students, recruited through a proportionate stratified convenient sampling technique, of the top 13 business institutions in Pakistan. The questionnaire was personally administered by visiting each institution with permission for data collection. A total of 554 responses were received and analyzed using the partial least squire-structural equation modeling approach.

The results exhibited that these business students perceived themselves as information literate. Furthermore, IL of business students appeared to predict positively their AE, CE and academic performance.

These results provided empirical and pragmatic insights for business educators, business librarians and accreditation bodies about IL effectiveness in academia. These findings may also inform policy and practice for IL instruction programs being carried out in business-related educational institutions not only in Pakistan but also in other countries of South Asia as they share similar characteristics.

This research would be a great contribution to the existing literature on IL, especially in the academic context as the interrelationship between IL, AE, CE and academic performance has not been investigated so far.

The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry.

The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises.

NLSPD is directly related to the degree of supply–demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM.

The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM.

NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.