Test of a mediation model of perceived organisational support

This study examined the mediating influence of trust in organization (TIO) and organization-based self-esteem (OBSE) on the relationship between perceived organization support (POS) and its work outcomes. Data were obtained from employee–supervisor dyads from multiple organizations located in a major city in southern China. Structural equation modeling results revealed that: (a) POS related to TIO and OBSE and (b) TIO and OBSE fully mediated the relationship between POS and the work outcomes of organizational commitment and in-role performance, but partially mediated the POS–organizational citizenship behavior relationship.

Simulation based knowledge elicitation:effect of visual representation and model parameters

Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

Material and efficient cause interpretations of the formative model:resolving misunderstandings and clarifying conceptual language

This paper presents a causal explanation of formative variables that unpacks and clarifies the generally accepted idea that formative indicators are ‘causes’ of the focal formative variable. In doing this, we explore the recent paper by Diamantopoulos and Temme (AMS Review, 3(3), 160-171, 2013) and show that the latter misunderstand the stance of Lee, Cadogan, and Chamberlain (AMS Review, 3(1), 3-17, 2013; see also Cadogan, Lee, and Chamberlain, AMS Review, 3(1), 38-49, 2013). By drawing on the multiple ways that one can interpret the idea of causality within the MIMIC model, we then demonstrate how the continued defense of the MIMIC model as a tool to validate formative indicators and to identify formative variables in structural models is misguided. We also present unambiguous recommendations on how formative variables can be modelled in lieu of the formative MIMIC model.

Low temperature 1,1,1-trichloroethane dehydrochlorination over Pt catalysts:from model surfaces to the real world

Fast X-ray photoelectron spectroscopy reveals efficient C–Cl activation of 1,1,1-trichloroethane occurs over platinum surfaces at 150 K, and in the presence of hydrogen, sustained ambient temperature dehydrochlorination to HCl and ethane is possible over supported Pt/Al2O3 catalysts.

Propene combustion over a model Pt/Al2O3/NiAl{110} catalyst

The genesis of a catalytically active model Pt/Al2O3/NiAl{110} oxidation catalyst is described. An ultrathin, crystalline γ-Al2O3 film was prepared via direct oxidation of a NiAl{110} single-crystal substrate. The room-temperature deposition of Pt clusters over the γ-Al2O3 film was characterised by LEED, AES and CO titration and follows a Stranski–Krastanov growth mode. Surface sulfation was attempted via SO2/O2 adsorption and thermal processing over bare and Pt promoted Al2O3/NiAl{110}. Platinum greatly enhances the saturation SOx coverage over that of bare alumina. Over clean Pt/γ-Al2O3 surfaces some adsorbed propene desorbs molecularly [similar]250 K while the remainder decomposes liberating hydrogen. Coadsorbed oxygen or sulfate promote propene combustion, with adsorbed sulfoxy species the most efficient oxidant. The chemistry of these alumina-supported Pt clusters shows a general evolution from small polycrystalline clusters to larger clusters with properties akin to low-index, Pt single-crystal surfaces.

Formative variables and unreal variables:why the formative MIMIC model is invalid

In this rejoinder, we provide a response to the three commentaries written by Diamantopoulos, Howell, and Rigdon (all this issue) on our paper The MIMIC Model and Formative Variables: Problems and Solutions (also this issue). We contrast the approach taken in the latter paper (where we focus on clarifying the assumptions required to reject the formative MIMIC model) by spending time discussing what assumptions would be necessary to accept the use of the formative MIMIC model as a viable approach. Importantly, we clarify the implications of entity realism and show how it is entirely logical that some theoretical constructs can be considered to have real existence independent of their indicators, and some cannot. We show how the formative model only logically holds when considering these ‘unreal’ entities. In doing so, we provide important counter-arguments for much of the criticisms made in Diamantopoulos’ commentary, and the distinction also helps clarify a number of issues in the commentaries of Howell and Rigdon (both of which in general agree with our original paper). We draw together these various threads to provide a set of conceptual tools researchers can use when thinking about the entities in their theoretical models.

The MIMIC model and formative variables:problems and solutions

The use of the multiple indicators, multiple causes model to operationalize formative variables (the formative MIMIC model) is advocated in the methodological literature. Yet, contrary to popular belief, the formative MIMIC model does not provide a valid method of integrating formative variables into empirical studies and we recommend discarding it from formative models. Our arguments rest on the following observations. First, much formative variable literature appears to conceptualize a causal structure between the formative variable and its indicators which can be tested or estimated. We demonstrate that this assumption is illogical, that a formative variable is simply a researcher-defined composite of sub-dimensions, and that such tests and estimates are unnecessary. Second, despite this, researchers often use the formative MIMIC model as a means to include formative variables in their models and to estimate the magnitude of linkages between formative variables and their indicators. However, the formative MIMIC model cannot provide this information since it is simply a model in which a common factor is predicted by some exogenous variables—the model does not integrate within it a formative variable. Empirical results from such studies need reassessing, since their interpretation may lead to inaccurate theoretical insights and the development of untested recommendations to managers. Finally, the use of the formative MIMIC model can foster fuzzy conceptualizations of variables, particularly since it can erroneously encourage the view that a single focal variable is measured with formative and reflective indicators. We explain these interlinked arguments in more detail and provide a set of recommendations for researchers to consider when dealing with formative variables.

Effect of Cu and Sn promotion on the catalytic deoxygenation of model and algal lipids to fuel-like hydrocarbons over supported Ni catalysts

The ability of Cu and Sn to promote the performance of a 20% Ni/Al2O3 catalyst in the deoxygenation of lipids to fuel-like hydrocarbons was investigated using model triglyceride and fatty acid feeds, as well as algal lipids. In the semi-batch deoxygenation of tristearin at 260 °C a pronounced promotional effect was observed, a 20% Ni-5% Cu/Al2O3 catalyst affording both higher conversion (97%) and selectivity to C10-C17 alkanes (99%) in comparison with unpromoted 20% Ni/Al2O3 (27% conversion and 87% selectivity to C10-C17). In the same reaction at 350 °C, a 20% Ni-1% Sn/Al2O3 catalyst afforded the best results, giving yields of C10-C17 and C17 of 97% and 55%, respectively, which contrasts with the corresponding values of 87 and 21% obtained over 20% Ni/Al2O3. Equally encouraging results were obtained in the semi-batch deoxygenation of stearic acid at 300 °C, in which the 20% Ni-5% Cu/Al2O3 catalyst afforded the highest yields of C10-C17 and C17. Experiments were also conducted at 260 °C in a fixed bed reactor using triolein − a model unsaturated triglyceride − as the feed. While both 20% Ni/Al2O3 and 20% Ni-5% Cu/Al2O3 achieved quantitative yields of diesel-like hydrocarbons at all reaction times sampled, the Cu-promoted catalyst exhibited higher selectivity to longer chain hydrocarbons, a phenomenon which was also observed in experiments involving algal lipids as the feed. Characterization of fresh and spent catalysts indicates that Cu enhances the reducibility of Ni and suppresses both cracking reactions and coke-induced deactivation.