Examining the Personal and Institutional Determinants of Research Productivity in Hospitality and Tourism Management

The transition toward a post-capitalist knowledge-oriented economy has resulted in an increasingly competitive academic environment, where the success of faculty is dependent on their research productivity. This study examines the personal and institutional determinants of the quantity and quality of the research productivity of hospitality and tourism management faculty in US institutions. A survey of 98 faculty found that a different set of determinants impact the quantity and quality aspects of research productivity. Also, institutional determinants were found to play a larger role, indicating the need for administrators to strive for a culture that is supportive of and an infrastructure that is conducive to their faculty’s research success. The authors use the field of hospitality and tourism management as a case study to develop a holistic and cohesive framework for knowledge worker productivity that can guide the evaluation, hiring, and development of researchers

A sufficient condition for a number to be the order of a nonsingular derivation of a Lie algebra

A study of the set N_p of positive integers which occur as orders of nonsingular derivations of finite-dimensional non-nilpotent Lie algebras of characteristic p>0 was initiated by Shalev and continued by the present author. The main goal of this paper is to show the abundance of elements of N_p. Our main result shows that any divisor n of q-1, where q is a power of p, such that $n\ge (p-1)^{1/p} (q-1)^{1-1/(2p)}$, belongs to N_p. This extends its special case for p=2 which was proved in a previous paper by a different method.Comment: 10 pages. This version has been revised according to a referee's suggestions. The additions include a discussion of the (lower) density of the set N_p, and the results of more extensive machine computations. Note that the title has also changed. To appear in Israel J. Mat

Evaluation and characterization of the methane-carbon dioxide decomposition reaction

A program was conducted to evaluate and characterize the carbon dioxide-methane (CO2-CH4) decomposition reaction, i.e., CO2 + CH4 = 2C + 2H2O. The primary objective was to determine the feasibility of applying this reaction at low temperatures as a technique for recovering the oxygen (O2) remaining in the CO2 which exits mixed with CH4 from a Sabatier CO2 reduction subsystem (as part of an air revitalization system of a manned spacecraft). A test unit was designed, fabricated, and assembled for characterizing the performance of various catalysts for the reaction and ultraviolet activation of the CH4 and CO2. The reactor included in the test unit was designed to have sufficient capacity to evaluate catalyst charges of up to 76 g (0.17 lb). The test stand contained the necessary instrumentation and controls to obtain the data required to characterize the performance of the catalysts and sensitizers tested: flow control and measurement, temperature control and measurement, product and inlet gas analysis, and pressure measurement. A product assurance program was performed implementing the concepts of quality control and safety into the program effort

'Datafication': Making sense of (big) data in a complex world

This is a pre-print of an article published in European Journal of Information Systems. The definitive publisher-authenticated version is available at the link below. Copyright @ 2013 Operational Research Society Ltd.No abstract available (Editorial

The history, evolution, and future of big data & analytics:A bibliometric analysis of its relationship to performance in organizations

Big data and analytics (BDA) are gaining momentum, particularly in the practitioner world. Research linking BDA to improved organizational performance seems scarce and widely dispersed though, with the majority focused on specific domains and/or macro-level relationships. In order to synthesize past research and advance knowledge of the potential organizational value of BDA, the authors obtained a data set of 327 primary studies and 1252 secondary cited papers. This paper reviews this body of research, using three bibliometric methods. First, it elucidates its intellectual foundations via co-citation analysis. Second, it visualizes the historical evolution of BDA and performance research and its substreams through algorithmic historiography. Third, it provides insights into the field's potential evolution via bibliographic coupling. The results reveal that the academic attention for the BDA-performance link has been increasing rapidly. The study uncovered ten research clusters that form the field's foundation. While research seems to have evolved following two main, isolated streams, the past decade has witnessed more cross-disciplinary collaborations. Moreover, the study identified several research topics undergoing focused development, including financial and customer risk management, text mining and evolutionary algorithms. The review concludes with a discussion of the implications for different functional management domains and the gaps for both research and practice.</p

A Factorization Algorithm for G-Algebras and Applications

It has been recently discovered by Bell, Heinle and Levandovskyy that a large class of algebras, including the ubiquitous $G$-algebras, are finite factorization domains (FFD for short). Utilizing this result, we contribute an algorithm to find all distinct factorizations of a given element $f \in \mathcal{G}$, where $\mathcal{G}$ is any $G$-algebra, with minor assumptions on the underlying field. Moreover, the property of being an FFD, in combination with the factorization algorithm, enables us to propose an analogous description of the factorized Gr\"obner basis algorithm for $G$-algebras. This algorithm is useful for various applications, e.g. in analysis of solution spaces of systems of linear partial functional equations with polynomial coefficients, coming from $\mathcal{G}$. Additionally, it is possible to include inequality constraints for ideals in the input

Big data-savvy teams’ skills, big data-driven actions and business performance

Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross-functional teams’ skills and its links to the role played by relevant data-driven actions and business performance. Drawing on the resource-based view (RBV) of the firm and on the data collected from big data experts working in global agrifood networks, we examine the links between the use of big data-savvy (BDS) teams’ skills, big data-driven (BDD) actions and business performance. BDS teams depend on multidisciplinary skills (e.g., computing, mathematics, statistics, machine learning, and business domain knowledge) that help them to turn their traditional business operations into modern data-driven insights (e.g., knowing real time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams' skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organisations that emphasise BDD actions perform better compared to those that do not focus on such applications and relevant insights

The Early Days of Research on Carbonic Anhydrase

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73862/1/j.1749-6632.1984.tb12310.x.pd

The least common multiple of a sequence of products of linear polynomials

Let $f(x)$ be the product of several linear polynomials with integer coefficients. In this paper, we obtain the estimate: $\log {\rm lcm}(f(1), ..., f(n))\sim An$ as $n\rightarrow\infty$, where $A$ is a constant depending on $f$.Comment: To appear in Acta Mathematica Hungaric