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Repertory grid technique is a well‐known and important tool for market research. Frost and Braine (1967) went as far as to say: “In our view, the Repertory Grid represents an approach of such fundamental importance that we regard it as having as much potential in market research as any technique since the invention of the questionnaire”. Grid technique has typically been used for identifying ideal product attributes. This article, however, gives an example of how the method was successfully used to investigate customers' views on a complex concept.

It seems to be well understood that the simultaneous import and export of goods which have different production functions, but which are aggregated into the same industry in classification schemes such as the SITC, is quite consistent with the standard trade theory of the Heckscher‐Ohlin‐Samuelson (HOS) model. For example, Grubel and Lloyd (1975, p.87) admit that two‐way trade in products such as wood and metal furniture, or nylon and wool yarn, which have similar end uses but different input requirements, can be explained readily by the HOS model (1979, p. 88). Gray explicitly distinguishes between “categorical aggregation” which occurs when there is two‐way trade in goods with different production functions and is consistent with the HOS model, and “true intra‐industry trade” which occurs when a country imports and exports “goods with virtually identical production functions”.

Access to daily store level scanner data has been increasingly easier in recent years in Japan and time series analysis based on a sales response model is becoming realistic. Introduces a new method of combining time series analysis and regression analysis on the price promotion effect, which enables simultaneous decomposition of store level scanner sales into trend (including seasonality), day‐of‐the‐week effect and explanatory variable effect due to price promotion. The method was applied to daily store level scanner sales of milk, showing evidence of the existence of day‐of‐the‐week effect. Further, a method of incorporating several kinds of price‐cut variables in regression analysis and the analyzed results were presented.

The purpose of this paper is to examine Philip B. Crosby’s 14 quality principles and analyze the interaction between them. Hitherto no research has been published on the implementation of total quality management (TQM) using Crosby’s 14 principles. To fill this gap, interpretive structural modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis have been designed to prioritize, sequence and categorize variables to find both the dependence and driving power of these variables.

At the initial stage experts from industry as well as from academia were contacted to provide an input for ISM methodology and examine interactions between identified variables. In this approach, interpretations of the interrelationships among variables have been discussed, whereas MICMAC analysis is used to discover dependence and driving power.

The results of the investigation revealed that “Management Commitment,” “Quality Improvement Team,” “Quality Awareness,” “Supervisor Training,” “Goal Setting” and “Cost of Quality Evaluation” are strategic requirements; “Corrective Action,” “Zero Defects Day” and “Error Cause Removal” are tactical requirements. “Recognition,” “Quality Measurement,” “Quality Councils” and “Do It Over Again” are operational requirements for TQM applications.

ISM is used as a part of this research to provide valuable insights into interrelationships among Crosby’s quality principles through a systematic framework. The research opens up a new focus area on the implementation of TQM for services as well as for the manufacturing industry.

The purpose of this paper model and prioritizes barriers to product development in medical device manufacturing industries using an integrated “structural equation modelling” (SEM) and “fuzzy technique for order performance by similarity to ideal solution” (FTOPSIS) framework.

Barriers to medical device development (MDD) are adopted from literature. The initial structural model is proposed, exploratory factor analysis and confirmatory factor analysis are used to determine factor loading and model fit, respectively. Further, FTOPSIS is used to rank the barriers and sensitivity analysis is carried to check the robustness of results. The results are discussed in detail and the recommendations to overcome the barriers are presented.

Barriers analysed and prioritized in this research significantly hinder the MDD. The expert survey is used to develop an initial structural equation model of barriers to MDD, find the reliability and validity of the model. Based on the opinion of the experts, the barriers are divided into three categories – internal, policy and induced barriers. FTOPSIS is applied to rank and prioritize the barriers based on views from these three classes of experts. More reliance on imported devices leading to increased imports (B11) and lack of uniform regulatory standards (B6) are found to have the highest rank together, indicating these to be the most important barriers from the perspective considered here. Sensitivity analysis indicates that the factors are less sensitive to the weights of criteria further confirming the reliability of the initial solution.

The prioritization of barriers may vary based upon experts. Policymakers, existing and new device developers need to give utmost importance to these barriers, which will help to accelerate the indigenous development of medical devices to overcome the present dependence on imports.

This paper demonstrates an integrated structural based modelling and prioritization technique for statistical modelling and prioritization of barriers to MDD. The results and recommendations will help policymakers and manufacturers to increase the indigenous share of medical devices. The integrated methodology can be effectively applied where the need for the combined quantitative and qualitative approach is there.

This paper demonstrates an effective structural based modelling and prioritization technique. It can be effectively applied in various fields, it will help policymakers and manufacturers to increase the indigenous share of medical devices.

THE orthodox solution of Lagrangian frequency equations involves the expansion into polynomial form of the characteristic determinantal equation in the latent roots, but this method becomes exceedingly laborious if a large number of frequencies and their associated modes are required accurately for any system of equations of high order, say above the sixth. We define a system of Lagrangian frequency equations to be of the nth order if it consists of n equations for n homogeneous unknowns, which we call modes. A useful contribution to the problem was made by the iteration solution of Duncan and Collar, which is especially valuable when only the highest one or two latent roots are required. But when an aircraft propeller vibration problem required the first seven frequencies and their associated modes for a 12th‐order equation whose coefficients involved a variable pitch angle, the labour of calculation by this method appeared at that time (1941) to be prohibitive. The ‘Escalator’ method was therefore devised jointly by the author and Captain J. Morris of the Royal Aircraft Establishment as an alternative. In the propeller problem all the latent roots involved were necessarily real. Dr L. Fox, using relaxation methods, has recently solved a similar problem in a remarkably short time. Unfortunately, relaxation methods cannot easily be extended to the case of complex latent roots, which can occur in connexion with flutter, radio circuits and other problems. In this paper it is shown how the Escalator method can be adapted without essential change to cases in which complex quantities occur.

This study aims to identify the marginal impact of introducing a signal attribute of pasture-raised beef on consumer willingness to pay (WTP) for other independent attributes.

The study is divided into two steps. The first, qualitative, consisted of investigating the values consumers have regarding beef production. To this end, 52 interviews with Brazilian and US consumers were conducted using laddering. In the second, quantitative, six experiments, (face to face and online) with 267 consumers of beef were performed.

As a result, the main value found for the Brazilians was security, while for the Americans was self-direction. For consumers, the WTP for animal welfare was the most important in the choice experiments where this information was present.

These findings offer an alternate beef differentiation, enabling it to be sold with higher added value by integrating these.

It is always of great importance for managers in organizations to evaluate their staff members and create incentive systems, using instruments such as Data Envelopment Analysis (DEA) and DEA-R (DEA models based on ratio analysis). The purpose of this paper is to propose a two-stage network incentives system for commercial banks.

Centralized Resource Allocation (CRA) models make it possible to project all decision-making units (DMUs) onto the efficient frontier by solving a single linear programming model. In this paper, we use our proposed DEA-R-based CRA models to evaluate commercial banks in a two-stage case when the only ratios available are the assets-to-costs and income-to-assets vectors.

Thirteen commercial banks modeled as two-stage networks were evaluated by the models proposed in two different cases of ratio data. Results suggest that the proposed methodology yields more accurate efficiency scores, thus allowing better discrimination among DMUs. Furthermore, evaluating the DMUs when they are structured as two-stage (or even three-stage) networks makes it possible to examine the incentives system in more detail. Therefore, the use of incentive systems by managers would allow a better focus on the priority activities of commercial banks and a faster movement toward the frontier of best practices.

The super-efficiency scores of a number of commercial banks are evaluated based on the CRA model, as a cornerstone criterion for the two-stage evaluation in DEA-R, thus allowing the rank of each commercial bank in terms of the incentives system rather on the performance of the productive process.

An eigenvalue method is presented for solving the transient heat conduction problem with time‐dependent or time‐independent boundary conditions. The spatial domain is divided into finite elements and at each finite element node, a closed‐form expression for the temperature as a function of time can be obtained. Three test problems which have exact solutions were solved in order to examine the merits of the eigenvalue method. It was found that this method yields accurate results even with a coarse mesh. It provides exact solution in the time domain and therefore has none of the time‐step restrictions of the conventional numerical techniques. The temperature field at any given time can be obtained directly from the initial condition and no time‐marching is necessary. For problems where the steady‐state solution is known, only a few dominant eigenvalues and their corresponding eigenvectors need to be computed. These features lead to great savings in computation time, especially for problems with long time duration. Furthermore, the availability of the closed form expressions for the temperature field makes the present method very attractive for coupled problems such as solid—fluid and thermal—structure interactions.