Impact of MBA Programs’ Business Analytics Breadth on Salary and Job Placement: The Role of University Ranking

Although many business schools have started to offer business analytics programs and courses for their MBA students, they lack understanding about how these efforts translate into job market gains for their graduates and whether all business schools have a level playing field. To bridge this gap, we use signaling theory to investigate the impacts that the business analytics breadth (BAB) level and university ranking of MBA programs have on graduates’ future employment success in terms of salary and job placement. We collected and analyzed data on business analytics-relevant courses that the top 89 business schools in the United States according to Bloomberg (bloomberg.com) offered. Our findings show the vital role of university ranking in determining the efficacy of BAB to produce job market gains for students: university ranking moderated the effect of business analytics offerings on post-graduation salary and job placement. These findings provide interesting insights for researchers and business schools interested in understanding the return on investment in business analytics programs

Piscataquis Cultural-Heritage Directory

https://digitalmaine.com/cultural_directories/1000/thumbnail.jp

04441 Abstracts Collection -- Mobile Information Management

From 24.10.04 to 29.10.04, the Dagstuhl Seminar 04441 ``Mobile Information Management\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Estimates and multivariable risk assessment of mid-buccal gingival recessions in an Italian adult population according to the 2018 World Workshop Classification System

Objectives: The aim of this cross-sectional study was to provide estimate of mid-buccal gingival recession (GR) according to the 2018 World Workshop Classification System and to explore GR risk indicators in a representative urban population in North-West of Italy. Material and methods: This is a secondary analysis using data collected in an epidemiological study enrolling a representative sample of 736 adults, living in Turin. GR prevalence was defined as the presence of at least one mid-buccal GR ≥ 1 mm. GRs were categorized according to the 2018 classification system (RT1, RT2, RT3) and to different severity cutoffs. Logistic regression analysis was performed to identify RT GR risk indicators. Results: Mid-buccal GR ≥ 1 mm affected 57.20% of subjects and 14.56% of teeth. When considering RT1 GRs, their prevalence was 40.90% and 6.29% at the patient and tooth level. RT2 and RT3 GRs affected 25.82% and 36.68% of the study population, respectively. RT1 GRs occurred mostly on maxillary and mandibular premolars and maxillary canines, while RT2 and RT3 GRs on maxillary molars and mandibular incisors. Older age, high education, and full-mouth plaque score (FMPS) 60% were significant contributors to RT2 and RT3 GRs. Conclusions: RT1 and RT3 are fairly common findings in this Italian population and are significantly associated to different contributing factors and tooth type distribution pattern. Clinical relevance: Prevention strategies should target different socio-demographic, behavioral, and clinical risk indicators based on the RT classes

Mustang Daily, April 4, 1973

Student newspaper of California Polytechnic State University, San Luis Obispo, CA.https://digitalcommons.calpoly.edu/studentnewspaper/2983/thumbnail.jp

Sentiment Analysis in Social Networks Using Social Spider Optimization Algorithm

In this study, a new swarm intelligence-based algorithm called Social Spider Algorithm (SSA), which is based on a simulation of the collaborative behaviours of spiders, was adapted for the first time for sentiment analysis (SA) within data obtained from Twitter. The SA problem was modelled as a search problem, with datasets considered as the search space and SSA modelled as a search strategy by determining an appropriate encoding scheme and objective function. The success of the SSA was compared with different Machine Learning (ML) algorithms within the same real datasets based on different metrics. Although this study is the first usage of SSA for the SA problem and there is no optimization for it, the attained results were promising and could provide new direction to related research about the use of optimized different artificial intelligence search algorithms for these types of online social network analysis problems. This study also introduced a new application domain for the optimization algorithms

The financialization of rented homes:continuity and change in housing financialization

This paper has two purposes: the first is to offer an empirical account of how rented homes have become more entangled in financial markets over the past two decades, particularly through the advent of real estate investment trusts (REITs) and listed real estate operating companies (REOCs). The second is to assess whether conceptualizing this as a process of “rental housing financialization” — distinct from but connected to the broader concepts of “housing financialization” and “financialization” — offers value to the scholarly community

Family ownership and control as drivers for environmental, social, and governance in family firms

Sluggish market demand can deteriorate the financial situation of a company and affect a shareholder's decision to adopt environmental, social, and governance criteria (ESG). According to the socioemotional wealth theory, family firms place significant emphasis on sustainable development and long-term orientation, but this emphasis can be either internally or externally driven according to the type of involvement chosen by the owning family. Therefore, this study uses listed family firms to explore the relationship between different types of family involvement (i.e., family ownership and control, the influence of market competition, and the institutionalisation level of the environment in which a firm decides to pursue ESG criteria). We performed a multivariate regression analysis on a sample of 1,151 Chinese companies to test these relationships and found that both family ownership and control are positively related to ESG scores. Market competition negatively moderates the influence of both family ownership and control on the adoption of ESG criteria. Moreover, the influence of family control is negatively moderated by the institutional environment. Thus, types of family involvement seem to be relevant for the firm's engagement with ESG criteria

Maine Invites You, 1985

https://digitalmaine.com/maine_invites_you/1033/thumbnail.jp