Innovation attributes and managers' decisions about the adoption of innovations in organizations: A meta-analytical review

The adop­tion of in­no­va­tions has emerged as a dom­i­nant re­search topic in the man­age­ment of in­no­va­tion in or­ga­ni­za­tions, al­though in­ves­ti­ga­tions of­ten yield mixed re­sults. To help man­agers and re­searchers im­prove their ef­fec­tive­ness, the au­thors em­ployed a meta-analy­sis in­te­grated with struc­tural equa­tion mod­el­ing to an­a­lyze the as­so­ci­a­tions be­tween the at­trib­utes of in­no­va­tions, man­agers' be­hav­ioral pref­er­ences, and or­ga­ni­za­tions' in­no­va­tion adop­tion de­ci­sions in a me­di­ated-mod­er­ated frame­work. Our find­ings of­fer ev­i­dence that at­trib­utes of in­no­va­tions in­flu­ence man­agers' be­hav­ioral pref­er­ences and, con­se­quently, adop­tion de­ci­sions in or­ga­ni­za­tions. We also ob­serve the sig­nif­i­cance of the con­text in which the adop­tion de­ci­sion oc­curs as well as the re­search set­tings em­ployed by schol­ars. Fi­nally, we dis­cuss the the­o­ret­i­cal con­tri­bu­tion and prac­ti­cal im­pli­ca­tions of our meta-an­a­lyt­i­cal re­sults

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the pattern by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game makes a decision among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information

Diffusion and entanglement of a kicked particle in an infinite square well under frequent measurements

We investigate the dynamics of a kicked particle in an infinite square well undergoing frequent measurements of energy. For a large class of periodic kicking force, constant diffusion is found in such a non-KAM system. The influence of phase shift of the kicking potential on the short-time dynamical behavior is discussed. The general asymptotical measurement-assisted diffusion rate is obtained. The entanglement between the particle and the measuring apparatus is investigated. There exist two distinct dynamical behaviors of entanglement. The bipartite entanglement grows with the kicking steps and it gains larger value for the more chaotic system. However, the pairwise entanglement between the system of interest and the partial spins of the measuring apparatus decreases with the kicking steps. The relation between the entanglement and quantum diffusion is also analyzed. PACS numbers: 05.45.Mt, 03.65.TaComment: 7 pages, 5 figures, RevTex4, Accepted by Phys. Rev.

Dynamics of trace metal sorption by an ion-exchange chelating resin described by a mixed intraparticle/film diffusion transport model. The Cd/Chelex case

The time-evolution of Cd2+ ion sorption by Chelex 100 resin was studied in batch experiments as a function of time, pH, ionic strength, stirring rate, mass of resin and initial metal ion concentration. In the experimental conditions, the amount of resin sites are in excess with respect to the amount of metal ion, leading to extensive depletion of metal in bulk solution when equilibrium is reached. The data were described using a mixed control mass transport model in finite volume conditions (MCM) that includes explicitly both intraparticle and film diffusion steps. Exact numerical computations and a new approximate analytical expression of this model are reported here. MCM successfully predicts the influence of pH and ionic strength on the experimental Cd(II)/Chelex kinetic profiles (which cannot be justified by a pure film diffusion controlled mechanism) with a minimum number of fitting parameters. The overall diffusion coefficient inside the resin was modelled in terms of the Donnan factor and the resin/cation binding stability constant. The values of the latter coefficient as a function of pH and ionic strength were estimated from the Gibbs-Donnan model. Even though MCM is numerically more involved than models exclusively restricted to film or intraparticle diffusion control, it proves to be accurate in a wider range of values of the mass transfer Biot number and solution/resin metal ratios.The authors gratefully acknowledge support for this research from the Spanish Ministry MINECO (Projects CTM2013-48967 and CTM2016-78798) and by the “Comissionat d'Universitats i Recerca de la Generalitat de Catalunya” (2014SGR1132). FQ acknowledges a grant from AGAUR