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The unprecedented growth of data available and the velocity at which it is collected has created a greater need for companies to seek employees who are able to use data and turn it into meaningful information that can be used to optimize management decision-making. Companies are viewing analytics and employees who can create and use them as essential for creating value. Analytics, however, is not a singular activity. Rather, it is focused on merging data from disparate corporate silos so that companies can maintain a competitive advantage. Companies today are seeking employees who understand the business domain in which decisions are made and who possess depth and breadth of understanding of the analytics to optimize decisions. But the reality is the demand for individuals grounded in analytics, particularly in data mining and predictive analytics, and with a solid foundation in a business discipline far exceeds the supply of graduates. Organizations who want to use analytics to gain competitive advantage are increasingly challenged in finding qualified talent (Harbart, 2013). Forty percent of respondents in a recent survey reported difficulty in attracting people in analytics and the same percentage said they struggled to retain analytics hires (Ransbotham, Kiron & Prentice, 2015). There are many drivers creating an urgent need for analytics skilled employees. Some of these include: (1) the continual exponential growth in structured and unstructured data, (2) the need to be able to draw competitive insights from data, (3) advances in analytics software and platforms, (4) the lack of skills in current employees for dealing with the complexities of big data, (5) increased demand to create and deploy predictive models that will lead to competitive differentiation, (6) increasing need for data security, scalability, and mobileenabled tools, and (7)) a need for employees who can translate data analyses into actions (IBM, 2015; Connolly, 2012; Loshin, 2012; eWeek, 2011; Shegel, 2015). One question facing all companies is what skills, knowledge and abilities should be sought in applicants for an analytics position. Job postings on LinkedIn for analytics positions in the United States were examined to determine the common skills sought by employers. There were more than 70,000 job postings on LinkedIn for analytics positions on June 5, 2016. These job postings were then culled into two categories that reflect the job prospects for new college graduates: (1) entry level (candidates with a baccalaureate degree) and (2) associate level (candidates with a master's or more advanced degree). A systematic sample of 150 of the postings sorted by relevance was taken. While the educational requirements were broad, i.e., rarely was a single discipline required, more than four-fifths of the positions listed mentioned specific degree requirements. A Bachelor's Degree in Statistics, Business, Math, Finance, Economics, Marketing Research or other quantitative oriented fields was required by 45% of job postings. Employers sought a master's or more advanced degree in Computer Science, Mathematics, Statistics, Quantitative Management, Econometrics, or in Business with a heavy analytics focus or the equivalent in training/experience in 37% of the job postings. The analysis resulted in two broad categories of skills required by employers: (1) Technical Competencies, to include software development/programming, statistical knowledge, quantitative analysis, and the ability to use a variety of analytical, statistical and modeling tools, and (2) Personal Traits and Abilities (to include communication skills, collaboration/team skills, ability to present analytical insights in an understandable way, creativity, curious nature to solve problems, etc. It should also be noted that domain expertise was pervasive throughout the jobs posted as companies expected candidates to have knowledge in the business and/or industry area identified for the position. While colleges and universities are beginning to prepare future business graduates with advanced analytics skills and abilities as well as possessing business acumen, the talent gap will not be filled overnight. Companies must be clear about what skills, knowledge and abilities are needed in analytics employees; and colleges and universities must work as a partner with corporations to prepare the next generation of analytics professionals. Colleges and universities must also provide continuing education and training to those already in analytics positions as the skills needed by analytics professionals five years ago will not be the skills required five years from now (Tubbs, 2014). [ABSTRACT FROM AUTHOR]

Group projects have become an integral part of many marketing courses. They are perceived by both practitioners and academicians as quite valuable and contribute significantly to a student's overall education and skill development (Bowen et al. 1994; Strong and Anderson 1990). Group projects provide many benefits to students to include: (1) additional information and multiple perspectives may lead to intellectual synergy and better understanding and retention of concepts (Goodsell et al. 1992), (2) opportunities for students to experience complex situations similar to what they might encounter when they enter the workforce (Goretesky 1984), (3) a social support system in which students share in the ownership of course content and learning (Alie et al. 1998), and (4) additional conventional benefits such as improved oral and written communication skills, enhanced interpersonal and technical skills, and experiencing multi-faceted projects (Williams, Beard, and Rymer 1991). It should be noted, however, that group projects are not an educational panacea and can have negative impacts on students such as free riding/social loafing, inadequate rewards for work performed, attitude problems, transaction costs in terms of time expenditures, and unequal participation (McCorkle et al. 1999). [ABSTRACT FROM AUTHOR]

International marketing managers should find the results of this study intriguing and helpful in their dealings with consumers in the Arab-Gulf States. Little research has focused on the ethical segmentation of foreign consumers in general, and those in the Arab region in particular. Thus, the findings from this study can be used to help multinational companies doing business in the region to be more culturally sensitive to how ethical decision-making is approached by different segments in the Arab-Gulf region. The results of this study have important implications for companies doing business in the Arab Gulf region. In some instances, Arab culture has been reputed to espouse different ethical values than what is valued in Western cultures. The results of this study, however, show that ethical judgments and behaviors also vary within the region. [ABSTRACT FROM AUTHOR]

The marketing literature suggests that a predisposition toward innovativeness may serve as a predictor of actual innovative behavior, especially within a given product domain. Past research has also shown relationships between a consumer's psychological traits (or personality characteristics) and innovative product/service adoption behavior. Previous studies, though, have left many gaps in this research stream. Although some research has examined the linkage between selected psychological constructs and innovative behavior, studies have typically only examined one or two personality variables at a time. Since consumers are more complex and are a composite of a myriad of traits, it is only appropriate that a variety of personality factors be examined concurrently. Research has also postulated that early adopters of new products and services have an innate innovativeness. That is, a psychological propensity to innovate, particularly in a specific product category. Yet, almost all of the studies to date, particularly those that marry innovativeness with personality traits, have focused solely on delineating which psychological variables best describe an innovator on a post-hoc basis (either based on a time-of-adoption or cross-sectional approach). A gap exists in determining the relationship between a consumer's psychological make-up and his or her innovative predisposition. Additionally, the empirical studies examining consumer innovativeness have typically lacked methodological rigor. This study addresses these issues through the use of a structural model which hypothesizes that (a) innovativeness predisposition is directly related to adoption behavior within a product class and (b) personality variables (specifically, fatalism, cognitive complexity and perceived risk) are directly related to innovativeness predisposition. [ABSTRACT FROM AUTHOR]