294 research outputs found
General Localization Lengths for Two Interacting Particles in a Disordered Chain
The propagation of an interacting particle pair in a disordered chain is
characterized by a set of localization lengths which we define. The
localization lengths are computed by a new decimation algorithm and provide a
more comprehensive picture of the two-particle propagation. We find that the
interaction delocalizes predominantly the center-of-mass motion of the pair and
use our approach to propose a consistent interpretation of the discrepancies
between previous numerical results.Comment: 4 pages, 2 epsi figure
Radiative Neutron-Proton Capture in Effective Chiral Lagrangians
We calculate the cross-section for the thermal
process in chiral perturbation theory to next-to-next-to-leading order using
heavy-fermion formalism. The exchange current correction is found to be
in amplitude and the chiral perturbation at one-loop order
gives the cross section \sigma_{th}^{np}=(334\pm 2)\ {\mbox mb} which is in
agreement with the experimental value (334.2\pm 0.5)\ {\mbox mb}. Together
with the axial charge transitions, this provides a strong support for the power
of chiral Lagrangians for nuclear physics.Comment: 9 pages, revtex, uses epsfig.sty, 2 uuencoded figure
Quantum computing of quantum chaos and imperfection effects
We study numerically the imperfection effects in the quantum computing of the
kicked rotator model in the regime of quantum chaos. It is shown that there are
two types of physical characteristics: for one of them the quantum computation
errors grow exponentially with the number of qubits in the computer while for
the other the growth is polynomial. Certain similarity between classical and
quantum computing errors is also discussed.Comment: revtex, 4 pages, 4 figure
Singular Cucker-Smale Dynamics
The existing state of the art for singular models of flocking is overviewed,
starting from microscopic model of Cucker and Smale with singular communication
weight, through its mesoscopic mean-filed limit, up to the corresponding
macroscopic regime. For the microscopic Cucker-Smale (CS) model, the
collision-avoidance phenomenon is discussed, also in the presence of bonding
forces and the decentralized control. For the kinetic mean-field model, the
existence of global-in-time measure-valued solutions, with a special emphasis
on a weak atomic uniqueness of solutions is sketched. Ultimately, for the
macroscopic singular model, the summary of the existence results for the
Euler-type alignment system is provided, including existence of strong
solutions on one-dimensional torus, and the extension of this result to higher
dimensions upon restriction on the smallness of initial data. Additionally, the
pressureless Navier-Stokes-type system corresponding to particular choice of
alignment kernel is presented, and compared - analytically and numerically - to
the porous medium equation
Spin relaxation of conduction electrons in bulk III-V semiconductors
Spin relaxation time of conduction electrons through the Elliot-Yafet,
D'yakonov-Perel and Bir-Aronov-Pikus mechanisms is calculated theoretically for
bulk GaAs, GaSb, InAs and InSb of both - and -type. Relative importance
of each spin relaxation mechanism is compared and the diagrams showing the
dominant mechanism are constructed as a function of temperature and impurity
concentrations. Our approach is based upon theoretical calculation of the
momentum relaxation rate and allows understanding of the interplay between
various factors affecting the spin relaxation over a broad range of temperature
and impurity concentration.Comment: an error in earlier version correcte
Customer relationship management: digital transformation and sustainable business model innovation
[EN] The point of departure for this study is the understanding of customer relationship management (CRM) as a set of technological solutions key for efficient business management, the benefits of which, highlighted by previous works, are presented and defined here as crucial for entrepreneurial success. Of particular interest for this purpose are the existing studies on sustainability, which provide a viable research model to assess and validate the potential effect of each CRM component (sales, marketing, and services) on the three dimensions of sustainability (economic, environmental, and social). Upon confirmation of our hypotheses, the subsequent validation of such model should bring a better understanding of the way in which CRM-related benefits may increase the positive impact of its components on each dimension of sustainability. CRM can hence be considered a sort of Green IT, oriented toward digital transformation and sustainable business model innovation. Indeed, this research model may be the basis for a more specific methodology to measure the impact and benefits of applying CRM, understood, as we will contend, both in terms of sustainable business models and innovation.Gil Gómez, H.; Guerola-Navarro, V.; Oltra Badenes, RF.; Lozano Quilis, JA. (2020). Customer relationship management: digital transformation and sustainable business model innovation. Economic Research-Ekonomska Istra ivanja. 33(1):2733-2750. https://doi.org/10.1080/1331677X.2019.1676283S27332750331Abson, D. J., Fischer, J., Leventon, J., Newig, J., Schomerus, T., Vilsmaier, U., … Lang, D. J. (2016). Leverage points for sustainability transformation. Ambio, 46(1), 30-39. doi:10.1007/s13280-016-0800-yAlegre, J., Sengupta, K., & Lapiedra, R. (2011). Knowledge management and innovation performance in a high-tech SMEs industry. International Small Business Journal: Researching Entrepreneurship, 31(4), 454-470. doi:10.1177/0266242611417472Arsić, S., Banjević, K., Nastasić, A., Rošulj, D., & Arsić, M. (2018). Family Business Owner as a Central Figure in Customer Relationship Management. Sustainability, 11(1), 77. doi:10.3390/su11010077Bose, R. (2002). Customer relationship management: key components for IT success. Industrial Management & Data Systems, 102(2), 89-97. doi:10.1108/02635570210419636Bradshaw, D., & Brash, C. (2001). Managing customer relationships in the e‐business world: how to personalise computer relationships for increased profitability. International Journal of Retail & Distribution Management, 29(12), 520-530. doi:10.1108/09590550110696969Cantner, U., Joel, K., & Schmidt, T. (2009). The use of knowledge management by German innovators. Journal of Knowledge Management, 13(4), 187-203. doi:10.1108/13673270910971923Chen, A. J. W., Boudreau, M., & Watson, R. T. (2008). Information systems and ecological sustainability. Journal of Systems and Information Technology, 10(3), 186-201. doi:10.1108/13287260810916907Chen, I. J., & Popovich, K. (2003). Understanding customer relationship management (CRM). Business Process Management Journal, 9(5), 672-688. doi:10.1108/14637150310496758Christofi, M., Leonidou, E., & Vrontis, D. (2015). Cause-related marketing, product innovation and extraordinary sustainable leadership: the root towards sustainability. Global Business and Economics Review, 17(1), 93. doi:10.1504/gber.2015.066533Chua, A. Y. ., & Banerjee, S. (2013). Customer knowledge management via social media: the case of Starbucks. Journal of Knowledge Management, 17(2), 237-249. doi:10.1108/13673271311315196Claycomb, C., Dröge, C., & Germain, R. (1999). The Effect of Just‐in‐Time with Customers on Organizational Design and Performance. The International Journal of Logistics Management, 10(1), 37-58. doi:10.1108/09574099910805923Cohen, W. M., & Levinthal, D. A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35(1), 128. doi:10.2307/2393553Stefanou, C. J., Sarmaniotis, C., & Stafyla, A. (2003). CRM and customer‐centric knowledge management: an empirical research. Business Process Management Journal, 9(5), 617-634. doi:10.1108/14637150310496721Damanpour, F. (1996). Organizational Complexity and Innovation: Developing and Testing Multiple Contingency Models. Management Science, 42(5), 693-716. doi:10.1287/mnsc.42.5.693Damanpour, F., & Evan, W. M. (1984). Organizational Innovation and Performance: The Problem of «Organizational Lag». Administrative Science Quarterly, 29(3), 392. doi:10.2307/2393031Dervitsiotis, K. N. (2010). Developing full-spectrum innovation capability for survival and success in the global economy. Total Quality Management & Business Excellence, 21(2), 159-170. doi:10.1080/14783360903549865Dewhurst, F., Martínez Lorente, A. R., & Dale, B. G. (1999). Total quality management and information technologies: an exploration of the issues. International Journal of Quality & Reliability Management, 16(4), 392-406. doi:10.1108/02656719910249333Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: what are they? Strategic Management Journal, 21(10-11), 1105-1121. doi:10.1002/1097-0266(200010/11)21:10/113.0.co;2-eEpiphany.com. (2001). CRM benefits. Retrieved from http://www.ephany.com/market/crm_benefits.html2001European Commission. (2013). One trillion euro to invest in Europe’s future—The EU’s budget framework 2014–2020. Retrieved from https://ec.europa.eu/regional_policy/en/newsroom/news/2013/11/one-trillion-euro-to-invest-in-europe-s-future-the-eu-s-budget-framework-2014-2020Fidel, P., Schlesinger, W., & Cervera, A. (2015). Collaborating to innovate: Effects on customer knowledge management and performance. Journal of Business Research, 68(7), 1426-1428. doi:10.1016/j.jbusres.2015.01.026FIDEL, P., SCHLESINGER, W., & EMILO, E. (2018). EFFECTS OF CUSTOMER KNOWLEDGE MANAGEMENT AND CUSTOMER ORIENTATION ON INNOVATION CAPACITY AND MARKETING RESULTS IN SMEs: THE MEDIATING ROLE OF INNOVATION ORIENTATION. International Journal of Innovation Management, 22(07), 1850055. doi:10.1142/s136391961850055xGallego, J., Rubalcaba, L., & Hipp, C. (2012). Organizational innovation in small European firms: A multidimensional approach. International Small Business Journal: Researching Entrepreneurship, 31(5), 563-579. doi:10.1177/0266242611430100Garbarino, E., & Johnson, M. S. (1999). The Different Roles of Satisfaction, Trust, and Commitment in Customer Relationships. Journal of Marketing, 63(2), 70-87. doi:10.1177/002224299906300205Gholami, H., Zameri Mat Saman, M., Mardani, A., Streimikiene, D., Sharif, S., & Zakuan, N. (2018). Proposed Analytic Framework for Student Relationship Management based on a Systematic Review of CRM Systems Literature. Sustainability, 10(4), 1237. doi:10.3390/su10041237Gibbert, M., Leibold, M., & Probst, G. (2002). Five Styles of Customer Knowledge Management, and How Smart Companies Use Them To Create Value. European Management Journal, 20(5), 459-469. doi:10.1016/s0263-2373(02)00101-9Gopalakrishnan, S., & Damanpour, F. (1997). A review of innovation research in economics, sociology and technology management. Omega, 25(1), 15-28. doi:10.1016/s0305-0483(96)00043-6Grawe, S. J., Chen, H., & Daugherty, P. J. (2009). The relationship between strategic orientation, service innovation, and performance. International Journal of Physical Distribution & Logistics Management, 39(4), 282-300. doi:10.1108/09600030910962249Huang, E. Y., & Lin, C. (2005). Customer‐oriented financial service personalization. Industrial Management & Data Systems, 105(1), 26-44. doi:10.1108/02635570510575171Huang, P.-S., & Shih, L.-H. (2008). Effective environmental management through environmental knowledge management. International Journal of Environmental Science & Technology, 6(1), 35-50. doi:10.1007/bf03326058Hult, G. T. M., & Ketchen, D. J. (2001). Does market orientation matter?: a test of the relationship between positional advantage and performance. Strategic Management Journal, 22(9), 899-906. doi:10.1002/smj.197Hult, G. T. M., Hurley, R. F., & Knight, G. A. (2004). Innovativeness: Its antecedents and impact on business performance. Industrial Marketing Management, 33(5), 429-438. doi:10.1016/j.indmarman.2003.08.015Karimi, J., Somers, T. M., & Gupta, Y. P. (2001). Impact of Information Technology Management Practices on Customer Service. Journal of Management Information Systems, 17(4), 125-158. doi:10.1080/07421222.2001.11045661King, S. F., & Burgess, T. F. (2008). Understanding success and failure in customer relationship management. Industrial Marketing Management, 37(4), 421-431. doi:10.1016/j.indmarman.2007.02.005Krizanova, A., Gajanova, L., & Nadanyiova, M. (2018). Design of a CRM Level and Performance Measurement Model. Sustainability, 10(7), 2567. doi:10.3390/su10072567Liao, S., Fei, W.-C., & Chen, C.-C. (2007). Knowledge sharing, absorptive capacity, and innovation capability: an empirical study of Taiwan’s knowledge-intensive industries. Journal of Information Science, 33(3), 340-359. doi:10.1177/0165551506070739Lin, R., Che, R., & Ting, C. (2012). Turning knowledge management into innovation in the high‐tech industry. Industrial Management & Data Systems, 112(1), 42-63. doi:10.1108/02635571211193635Lopez-Nicolas, C., & Molina-Castillo, F. J. (2008). Customer Knowledge Management and E-commerce: The role of customer perceived risk. International Journal of Information Management, 28(2), 102-113. doi:10.1016/j.ijinfomgt.2007.09.001March, J. G. (1991). Exploration and Exploitation in Organizational Learning. Organization Science, 2(1), 71-87. doi:10.1287/orsc.2.1.71Massey, A. P., Montoya-Weiss, M. M., & Holcom, K. (2001). Re-engineering the customer relationship: leveraging knowledge assets at IBM. Decision Support Systems, 32(2), 155-170. doi:10.1016/s0167-9236(01)00108-7Mckenzie, C. R. M., & Liersch, M. J. (2011). Misunderstanding Savings Growth: Implications for Retirement Savings Behavior. Journal of Marketing Research, 48(SPL), S1-S13. doi:10.1509/jmkr.48.spl.s1Menguc, B. (2006). Creating a Firm-Level Dynamic Capability through Capitalizing on Market Orientation and Innovativeness. Journal of the Academy of Marketing Science, 34(1), 63-73. doi:10.1177/0092070305281090Mishra, D., Akman, I., & Mishra, A. (2014). Theory of Reasoned Action application for Green Information Technology acceptance. Computers in Human Behavior, 36, 29-40. doi:10.1016/j.chb.2014.03.030Molla, A. & Abareshi, A. (2011). Green IT adoption: A motivational perspective. In Proceedings of the 15th Pacific Asia Conference on Information Systems, Brisbane, QLD, Australia, 7–11 July; p. 137.Introductory Chapter: Framework for Energy and Environmental Management in Industry. (s. f.). Applied Industrial Energy and Environmental Management, 1-22. doi:10.1002/9780470714379.chNgo, L. V., & O’Cass, A. (2012). In Search of Innovation and Customer-related Performance Superiority: The Role of Market Orientation, Marketing Capability, and Innovation Capability Interactions. Journal of Product Innovation Management, 29(5), 861-877. doi:10.1111/j.1540-5885.2012.00939.xPanayides, P. (2006). Enhancing innovation capability through relationship management and implications for performance. European Journal of Innovation Management, 9(4), 466-483. doi:10.1108/14601060610707876Pohludka, M., Stverkova, H., & Ślusarczyk, B. (2018). Implementation and Unification of the ERP System in a Global Company as a Strategic Decision for Sustainable Entrepreneurship. Sustainability, 10(8), 2916. doi:10.3390/su10082916Prahalad, C. K., & Ramaswamy, V. (2004). Co‐creating unique value with customers. Strategy & Leadership, 32(3), 4-9. doi:10.1108/10878570410699249Rao, H., & Drazin, R. (2002). OVERCOMING RESOURCE CONSTRAINTS ON PRODUCT INNOVATION BY RECRUITING TALENT FROM RIVALS: A STUDY OF THE MUTUAL FUND INDUSTRY, 1986-94. Academy of Management Journal, 45(3), 491-507. doi:10.2307/3069377Robson, P. J. A., & Bennett, R. J. (2000). Small Business Economics, 15(3), 193-208. doi:10.1023/a:1008129012953Rollins, M. & Halinen, A. (2005). Customer knowledge management competence: Towards a theoretical framework. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences, Hawaii (pp. 1–10). IEEE.Romano, A. C. Jr (2000). Customer relations management in information systems research. In H. M. Chung (Ed.), Proceedings of the Americas Conference in Information Systems (AMCIS), Long Beach, California, 10–13 August, pp. 811–819.Romano Jr, N. C., & Fjermestad, J. (2001). Electronic Commerce Customer Relationship Management: An Assessment of Research. International Journal of Electronic Commerce, 6(2), 61-113. doi:10.1080/10864415.2001.11044232Sahay, B. S., & Ranjan, J. (2008). Real time business intelligence in supply chain analytics. Information Management & Computer Security, 16(1), 28-48. doi:10.1108/09685220810862733Scullin, S., Allora, J., Lloyd, G. O. & Fjermestad, J. (2002). Electronic customer relationship management: Benefits, considerations, pitfalls and trends. In Proceedings of the IS One World Conference, Las Vegas, Nevada, April, pp. 3–5.Shane, S. A., & Ulrich, K. T. (2004). 50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship inManagement Science. Management Science, 50(2), 133-144. doi:10.1287/mnsc.1040.0204Sims, D. (2000). A new ROI for new economy CRM and just why doesn’t high-tech get it? crmguru.com, April 2000.Sin, L. Y. M., Tse, A. C. B., & Yim, F. H. K. (2005). CRM: conceptualization and scale development. European Journal of Marketing, 39(11/12), 1264-1290. doi:10.1108/03090560510623253Tushman, M. L. (1997). Winning through innovation. Strategy & Leadership, 25(4), 14-19. doi:10.1108/eb054591Verhoef, P. C., & Donkers, B. (2001). Predicting customer potential value an application in the insurance industry. Decision Support Systems, 32(2), 189-199. doi:10.1016/s0167-9236(01)00110-5Vorhies, D. W., & Harker, M. (2000). The Capabilities and Perfor Mance Advantages of Market‐Driven Firms: An Empirical Investigation. Australian Journal of Management, 25(2), 145-171. doi:10.1177/031289620002500203Waltner, C. (2001). CRM makes on-line shopping personal. InformationWeek, January 29, 2001.Weerawardena, J. (2003). Exploring the role of market learning capability in competitive strategy. European Journal of Marketing, 37(3/4), 407-429. doi:10.1108/03090560310459023Whatis.com. (2001). DIY BI: A guide to self-service business intelligence implementation. Retrieved from http://whatis.techtarget.com/whatis_definition_page/0,4152,211901,00.htmlZhu, Z., & Nakata, C. (2007). Reexamining the Link Between Customer Orientation and Business Performance: The Role of Information Systems. Journal of Marketing Theory and Practice, 15(3), 187-203. doi:10.2753/mtp1069-667915030
New anomalous trajectory in Regge theory
We show that a new Regge trajectory with \alpha_{f_1} (0) \approx 1 and slope
\alpha_{f_1}'(0) \approx 0 explains the features of hadron-hadron scattering
and photoproduction of the rho and phi mesons at large energy and momentum
transfer. This trajectory with quantum numbers P = C = +1 and odd signature can
be considered as a natural partner of the Pomeron which has even signature. The
odd signature of the new exchange leads to contributions to the spin-dependent
cross sections, which do not vanish at large energy. The links between the
anomalous properties of this trajectory, the axial anomaly and the flavor
singlet axial vector f_1 (1285) meson are discussed.Comment: 20 pages, REVTeX, 8 figures (9 eps files), version to appear in Phys.
Rev.
The role of TNF genetic variants and the interaction with cigarette smoking for gastric cancer risk: a nested case-control study
<p>Abstract</p> <p>Background</p> <p>The aim of this study was to investigate the role of <it>TNF </it>genetic variants and the combined effect between <it>TNF </it>gene and cigarette smoking in the development of gastric cancer in the Korean population.</p> <p>Methods</p> <p>We selected 84 incident gastric cancer cases and 336 matched controls nested within the Korean Multi-Center Cancer Cohort. Six SNPs on the <it>TNF </it>gene, <it>TNF</it>-α-238 G/A, -308 G/A, -857 C/T, -863 C/A, -1031 T/C, and <it>TNF</it>-β 252 A/G were genotyped. The ORs (95% CIs) were calculated using unconditional logistic regression model to detect each SNP and haplotype-pair effects for gastric cancer. The combined effects between the <it>TNF </it>gene and smoking on gastric cancer risk were also evaluated. Multi dimensionality reduction (MDR) analyses were performed to explore the potential <it>TNF </it>gene-gene interactions.</p> <p>Results</p> <p><it>TNF</it>-α-857 C/T containing the T allele was significantly associated with an increased risk of gastric cancer and a linear trend effect was observed in the additive model (OR = 1.6, 95% CI 1.0–2.5 for CT genotype; OR = 2.6, 95% CI 1.0–6.4 for TT genotype). All haplotype-pairs that contained TCT or CCC of <it>TNF</it>-α-1031 T/C, <it>TNF</it>-α-863 C/A, and <it>TNF</it>-α-857 C/T were associated with a significantly higher risk for gastric cancer only among smokers. In the MDR analysis, regardless of smoking status, <it>TNF</it>-α-857 C/T was included in the first list of SNPs with a significant main effect.</p> <p>Conclusion</p> <p><it>TNF</it>-α-857 C/T polymorphism may play an independent role in gastric carcinogenesis and the risk for gastric cancer by <it>TNF </it>genetic effect is pronounced by cigarette smoking.</p
Heavy Quark Symmetry and the Skyrme Model
We present a consistent way of describing heavy baryons containing a heavy
quark as bound states of an soliton and heavy mesons. The resulting
mass formula reveals the heavy quark symmetry explicitly. By extending the
model to the orbitally excited states, we establish the generic structure of
the heavy baryon spectrum. As anticipated from the heavy quark spin symmetry,
the -factor denoting the hyperfine splitting constant {\em vanishes} and the
baryons with the same angular momentum of light degrees of freedom form
degenerate doublets. This approach is also applied to the pentaquark exotic
baryons, where the conventional -factor plays no more a role of the
hyperfine constant. After diagonalizing the Hamiltonian of order , we
get the degenerate doublets, which implies the vanishing of genuine hyperfine
splitting.Comment: REVTeX, 33 pages, 3 figures included, SNUTP-94/13 (revised
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