An examination of moderator effects in the four-stage loyalty model

Oliver’s 1997 four-stage loyalty model proposes that loyalty consists of belief, affect, intention, and action. Although this loyalty model has recently been subject to empirical examination, the issue of moderator variables has been largely neglected. This article fills that void by analyzing the moderating effects of selected personal and situational characteristics, using a sample of 888 customers of a large do-it-yourself retailer. The results of multi-group causal analysis suggest that these moderators exert an influence on the development of the different stages of the loyalty sequence. Specifically, age, income, education and expertise, price orientation, critical incident recovery, and loyalty card membership are found to be important moderators of the links in the four-stage loyalty model. Limitations of the study are outlined, and implications for both research and managerial practice are discussed.

Switching barriers in the four-stage loyalty model

Oliver (1997) suggests a four-stage loyalty model proposing that loyalty consists of belief, affect, intentions, and action. Although this model has recently been subject to empirical examination, the issue of moderator variables has been largely neglected. This article fills that void by analyzing the moderating effects of switching barriers, using a sample of 589 customers of a large do-it-yourself (DIY) retailer. The results suggest that these moderators exert an influence on the development of the different stages of the loyalty sequence. Specifically, switching costs, social benefits, and attractiveness of alternatives are found to be important moderators of the links in the four-stage loyalty model.

Optimisation of two-stage raman converter based on phosphosilicate core fibre:Modelling and experiment

Parameter optimization of a two-stage Raman fibre converters (RFC) based on phosphosilicate core fiber was presented. The optimal operational regime was determined and tolerance of the converter against variations of laser parameters was analyzed. Converter was pumped by ytterbium-doped double-clad fibre laser with a maximum output power of 3.8W at 1061 nm. A phosphosilicate-core RFC with enhanced performance was fabricated using the results of numerical modelling.

A stage-oriented model (SOM) for e-commerce adoption:a study of Saudi Arabian organisations

Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.

CVaR minimization by the SRA algorithm

Using the risk measure CV aR in �nancial analysis has become more and more popular recently. In this paper we apply CV aR for portfolio optimization. The problem is formulated as a two-stage stochastic programming model, and the SRA algorithm, a recently developed heuristic algorithm, is applied for minimizing CV aR.

A Two-stage Bertrand-Edgeworth Game

In our investigation we are expanding a Bertrand-Edgeworth duopoly into a two-stage game in which during the first stage the firms can select their rationing rule. We will show that under certain conditions the efficient rationing rule is an equilibrium action of the first stage.

CVaR számítás SRA algoritmussal (CVaR minimization by the SRA algorithm)

A CV aR kockázati mérték egyre nagyobb jelentőségre tesz szert portfóliók kockázatának megítélésekor. A portfolió egészére a CVaR kockázati mérték minimalizálását meg lehet fogalmazni kétlépcsős sztochasztikus feladatként. Az SRA algoritmus egy mostanában kifejlesztett megoldó algoritmus sztochasztikus programozási feladatok optimalizálására. Ebben a cikkben az SRA algoritmussal oldottam meg CV aR kockázati mérték minimalizálást. ___________ The risk measure CVaR is becoming more and more popular in recent years. In this paper we use CVaR for portfolio optimization. We formulate the problem as a two-stage stochastic programming model. We apply the SRA algorithm, which is a recently developed heuristic algorithm, to minimizing CVaR.

Parallel nonconvex generalized Benders decomposition for natural gas production network planning under uncertainty

A scenario-based two-stage stochastic programming model for gas production network planning under uncertainty is usually a large-scale nonconvex mixed-integer nonlinear programme (MINLP), which can be efficiently solved to global optimality with nonconvex generalized Benders decomposition (NGBD). This paper is concerned with the parallelization of NGBD to exploit multiple available computing resources. Three parallelization strategies are proposed, namely, naive scenario parallelization, adaptive scenario parallelization, and adaptive scenario and bounding parallelization. Case study of two industrial natural gas production network planning problems shows that, while the NGBD without parallelization is already faster than a state-of-the-art global optimization solver by an order of magnitude, the parallelization can improve the efficiency by several times on computers with multicore processors. The adaptive scenario and bounding parallelization achieves the best overall performance among the three proposed parallelization strategies.

A Two-Stage Online Approach for Collaborative Multi-Agent Planning under Uncertainty

In a team of multiple agents, the pursuance of a common goal is a defining characteristic. Since agents may have different capabilities, and effects of actions may be uncertain, a common goal can generally only be achieved through a careful cooperation between the different agents. In this work, we propose a novel two-stage planner that combines online planning at both team level and individual level through a subgoal delegation scheme. The proposal brings the advantages of online planning approaches to the multi-agent setting. A number of modifications are made to a classical UCT approximate algorithm to (i) adapt it to the application domains considered, (ii) reduce the branching factor in the underlying search process, and (iii) effectively manage uncertain information of action effects by using information fusion mechanisms. The proposed online multi-agent planner reduces the cost of planning and decreases the temporal cost of reaching a goal, while significantly increasing the chance of success of achieving the common goal. 

Heuristics for the two-stage job shop scheduling problem with a bottleneck machine

Abstract not available

Two-stage open shop scheduling with a bottleneck machine

Abstract not available

Sustainable deployment of QTLs conferring quantitative resistance to crops: first lessons from a stochastic model

International audience

Vehicle routing and location routing problems with minimum latency: algorithms and models

Latency can be defined as the sum of the arrival times at the customers. Minimum latency problems are specially relevant in applications related to humanitarian logistics. This thesis presents algorithms for solving a family of vehicle routing problems with minimum latency. First the latency location routing problem (LLRP) is considered. It consists of determining the subset of depots to be opened, and the routes that a set of homogeneous capacitated vehicles must perform in order to visit a set of customers such that the sum of the demands of the customers assigned to each vehicle does not exceed the capacity of the vehicle. For solving this problem three metaheuristic algorithms combining simulated annealing and variable neighborhood descent, and an iterated local search (ILS) algorithm, are proposed. Furthermore, the multi-depot cumulative capacitated vehicle routing problem (MDCCVRP) and the multi-depot k-traveling repairman problem (MDk-TRP) are solved with the proposed ILS algorithm. The MDCCVRP is a special case of the LLRP in which all the depots can be opened, and the MDk-TRP is a special case of the MDCCVRP in which the capacity constraints are relaxed. Finally, a LLRP with stochastic travel times is studied. A two-stage stochastic programming model and a variable neighborhood search algorithm are proposed for solving the problem. Furthermore a sampling method is developed for tackling instances with an infinite number of scenarios. Extensive computational experiments show that the proposed methods are effective for solving the problems under study.

Structure-hepatic disposition relationships for cationic drugs in isolated perfused rat livers: Transmembrane exchange and cytoplasmic binding process

This work studied the structure-hepatic disposition relationships for cationic drugs of varying lipophilicity using a single-pass, in situ rat liver preparation. The lipophilicity among the cationic drugs studied in this work is in the following order: diltiazem. propranolol. labetalol. prazosin. antipyrine. atenolol. Parameters characterizing the hepatic distribution and elimination kinetics of the drugs were estimated using the multiple indicator dilution method. The kinetic model used to describe drug transport (the two-phase stochastic model) integrated cytoplasmic binding kinetics and belongs to the class of barrier-limited and space-distributed liver models. Hepatic extraction ratio (E) (0.30-0.92) increased with lipophilicity. The intracellular binding rate constant (k(on)) and the equilibrium amount ratios characterizing the slowly and rapidly equilibrating binding sites (K-S and K-R) increase with the lipophilicity of drug (k(on) : 0.05-0.35 s(-1); K-S : 0.61-16.67; K-R : 0.36-0.95), whereas the intracellular unbinding rate constant (k(off)) decreases with the lipophilicity of drug (0.081-0.021 s(-1)). The partition ratio of influx (k(in)) and efflux rate constant (k(out)), k(in)/k(out), increases with increasing pK(a) value of the drug [from 1.72 for antipyrine (pK(a) = 1.45) to 9.76 for propranolol (pK(a) = 9.45)], the differences in k(in/kout) for the different drugs mainly arising from ion trapping in the mitochondria and lysosomes. The value of intrinsic elimination clearance (CLint), permeation clearance (CLpT), and permeability-surface area product (PS) all increase with the lipophilicity of drug [CLint (ml . min(-1) . g(-1) of liver): 10.08-67.41; CLpT (ml . min(-1) . g(-1) of liver): 10.80-5.35; PS (ml . min(-1) . g(-1) of liver): 14.59-90.54]. It is concluded that cationic drug kinetics in the liver can be modeled using models that integrate the presence of cytoplasmic binding, a hepatocyte barrier, and a vascular transit density function.