Multicriteria analysis in agricultural marketing: The case of French olive oil market

Agribusiness industries face a stiff competition originating mainly from the EU trade barrier’s removal and the rapidly changing marketing environment of the single European market. Therefore, certain need has been identified towards the development and proper utilization of updated market research tools and methodologies in the field of agricultural marketing. The aim of this paper is to show the usefulness of multicriteria approach in analyzing consumer’s preference data and its ability to support new product development processes by agricultural firms. The paper outlines first the philosophy of agricultural marketing by emphasizing on the features, which differentiate it from general marketing. Several methodological issues in agricultural marketing are then presented through a state-of-the art survey. Then, the paper develops a consumer-based methodology to support product development decisions where the key-role is played to determine the preference model which explains a single consumer’s ranking; a decision support system summarizes the analysis on the whole set of interviewed consumers to prescribe the `ideal' profile of a new product and to simulate its penetration strategy into the market. Results from the application of the methodology to a survey data base coming from the Paris olive oil market are presented. Finally, the paper concludes with some recommendations about marketing practice in agribusiness.     

Fuzzy linear programming models for NPD using a four-phase QFD activity process based on the means-end chain concept

Quality function deployment (QFD) is a customer-driven approach in processing new product development (NPD) to maximize customer satisfaction. Determining the fulfillment levels of the “hows”, including design requirements (DRs), part characteristics (PCs), process parameters (PPs) and production requirements (PRs), is an important decision problem during the four-phase QFD activity process for new product development. Unlike previous studies, which have only focused on determining DRs, this paper considers the close link between the four phases using the means-end chain (MEC) concept to build up a set of fuzzy linear programming models to determine the contribution levels of each “how” for customer satisfaction. In addition, to tackle the risk problem in NPD processes, this paper incorporates risk analysis, which is treated as the constraint in the models, into the QFD process. To deal with the vague nature of product development processes, fuzzy approaches are used for both QFD and risk analysis. A numerical example is used to demonstrate the applicability of the proposed model.     

Goal programming model: A glorious history and a promising future

In the last 40 years, there has been a marked transformation in the development of new methodologies to assist the decision-making process, especially in the development of procedures in multi-criterion decision-making and in multi-objective programming (MOP). Goal programming (GP) is the most commonly known model of MOP and it is today alive more than ever, supported by a network of researchers and practitioners continually feeding it with theoretical developments and applications, all of these with resounding success. This paper paints a picture summarizing the history of GP and suggests a few areas of research in this era of globalization.     

Models for concurrent product and process design

We propose procedures to address product design and manufacturing process configurations concurrently in environments characterized by large degrees of product proliferation. Exploiting the intrinsic flexibility of product and process design, we present two approaches that synchronize production flows through the manufacturing system. These approaches integrate product and manufacturing system design decisions with operational concerns and provide powerful means for managing production in environments characterized by a proliferation of products. Experimental results show that the proposed methods can substantially reduce manufacturing lead times, work in process (WIP), and overall system complexity.     

The use of optimisation for enhancing the development of a novel sustainable masonry unit

This paper examines whether it is possible to utilise optimisation techniques to enhance the efficiency of the experiment-based development of a new product. Conventionally, a laboratory-based experimental investigation requires to check all combinations of all independent parameters describing the product; hence the optimum levels of the tested parameters is obtained. As a result there may be many thousands of samples produced to optimise these parameters; this is a time consuming, costly and laborious process. Instead, it is suggested that an empirical model is established and validated using the results of the laboratory investigation making it suitable for optimisation.     

Economic lot scheduling problem with imperfect production processes and setup times

Deteriorating production processes are common in reality. Although every production process starts in an ‘in-control’ state to produce items of acceptable quality, it may shift to an ‘out-of-control’ state, owing to ageing, at any random time and produce defective items. In the present article, we study the Economic Lot Scheduling Problem (ELSP) with imperfect production processes having significant changeovers between the products. The mathematical models are developed for the ELSP using both the common cycle approach and the time-varying lot sizes approach, taking into account the effects of imperfect quality and process restoration. Numerical examples are cited to illustrate the solution procedures and to compare the performances of the solution methodologies adopted to solve the ELSP.     

OR at Work in Modern Manufacturing

By describing the industrial assembly of a real product, methodologies and considerations are discussed for the re-alignment of discrete assembly systems in line with modern standards. Poor manufacturing procedures are highlighted, and a number of alternative strategies for system replacement are presented. A decision tree is used to categorize assembly into one of three types, and an integrated solution is proposed. The possible financial benefits, essential to maintain market position, are identified for each stage of an evolutionary cycle of continuous product design and changing manufacturing methods.     

A production–inventory model in an imperfect production process

The paper develops a model to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process. The basic assumption of the classical Economic Manufacturing Quantity (EMQ) model is that all manufacturing items are of perfect quality. The assumption is not true in practice. Most of the production system produces perfect and imperfect quality items. In some cases the imperfect quality (non conforming) items are reworked at a cost to restore its quality to the original one. Rework cost may be reduced by improvements in product reliability (i.e., decreasing in product reliability parameter). Lower value of product reliability parameter results in increase development cost of production and also smaller quantity of nonconforming products. The unit production cost is a function of product reliability parameter and production rate. As a result, higher development cost increases unit production cost. The problem of optimal planning work and rework processes belongs to the broad field of production–inventory model which deals with all kinds of reuse processes in supply chains. These processes aim to recover defective product items in such a way that they meet the quality level of ‘good item’. The benefits from imperfect quality items are: regaining the material and value added on defective items and improving the environment protection. In this point of view, a model is introduced here to guide a firm/industry in addressing variable product reliability factor, variable unit production cost and dynamic production rate for time-varying demand. The paper provides an optimal control formulation of the problem and develops necessary and sufficient conditions for optimality of the dynamic variables. In this purpose, the Euler–Lagrange method is used to obtain optimal solutions for product reliability parameter and dynamic production rate. Finally, numerical examples are given to illustrate the proposed model.     

Product line selection and pricing analysis: Impact of genetic relaxations

A model for the product line selection and pricing problem (PLSP) is presented andthree solution procedures based on a genetic algorithm are developed to analyze the results based on consumer preference patterns. Since the PLSP model is nonlinear and integer, two of the solution procedures use genetic encoding to “relax” the NP hard model. The relaxations result in linear integer and shortest path models for the fitness evaluation which are solved using branch and bound and labeling algorithms, respectively. Performance of the quality of solutions generated by the procedures is evaluated for various problem sizes and customer preference structures. The results show that the genetic relaxations provide efficient and effective solution methodologies for the problem, when compared to the pure artificial intelligence technique of genetic search. The impact of the preference structure on the product line and the managerial implications of the solution characteristics generated by the genetic relaxations are also discussed. The models can be used to explicitly consider tradeoffs between marketing and operations concerns in designing a product line.     

A survey of algorithmic methods for partially observed Markov decision processes

A partially observed Markov decision process (POMDP) is a generalization of a Markov decision process that allows for incomplete information regarding the state of the system. The significant applied potential for such processes remains largely unrealized, due to an historical lack of tractable solution methodologies. This paper reviews some of the current algorithmic alternatives for solving discrete-time, finite POMDPs over both finite and infinite horizons. The major impediment to exact solution is that, even with a finite set of internal system states, the set of possible information states is uncountably infinite. Finite algorithms are theoretically available for exact solution of the finite horizon problem, but these are computationally intractable for even modest-sized problems. Several approximation methodologies are reviewed that have the potential to generate computationally feasible, high precision solutions.     

Managing the exchange of information in product development

In the present paper, we develop a dynamic programming (DP) model of the product development (PD) process. We conceptualize product development as a sequence of decisions: whether to incorporate a piece of information that just arrived (i.e. became available) or wait longer. We utilize this formulation to analyze different situations that depend on the type, and nature of information that is exchanged: stationary versus dynamic information. We derive optimal decision rules to determine whether (and when) to incorporate for each case. An analysis of the model results in several important findings. First, we must not necessarily incorporate all available information that is related to the design activity. Specifically, once the information collection exceeds certain value, the design team should stop collecting further information. Second, only when past design work accumulates to a certain threshold value should the team include the latest information and perform rework. Large uncertainty of the information and large sensitivity of the design activity makes the incorporation of new information less likely. Finally, managerial implications are discussed with several numerical examples.     

Organizing product releases in time-driven development processes: a probabilistic analysis

In this paper, the problem is addressed of how to organizea new product development process that is fast on the one handand that provides good-quality results on the other hand. Severalplanning techniques, like PERT and CPM, are available to analysethe completion time or product release time of such complexprocesses. Although these techniques are all well known andare widely used in project management, they do not address theiterative mode of operation that is characteristic for suchuncertain processes. Neither do they offer a tool or guidelinesto ‘design’ a composition of iterative processesbecause they are analytical. In this paper, a quantitative concept is presented for modellingthe release time of a single uncertain iterative activity, asa random variable to deal with the probabilistic aspect in asimple way. From this simple model, the complexity is extendedsystematically to model fundamentally different configurations,that are on the one hand simple enough to be studied analyticallyand on the other hand exhibit their fundamentally differentrelease characteristics, as experienced in real life. From theanalysis, guidelines are formulated for organizing or (re)configuringa complex process configuration. It is demonstrated that organizing uncertain processes fora fast product release requires a balance between the exploitationof the principles of concurrent engineering and the risk ofoverrunning time targets. An important factor in this balanceis the decision structure for the release of intermediate results.The ‘empowerment’ structure, a structure where decisionsare not clustered as milestones but are made without any delay,offers great opportunity in terms of small mean release timesand small variances thereof.     

Fuzzy linear programming models for new product design using QFD with FMEA

Quality function deployment (QFD) is a customer-driven approach in processing new product developments in order to maximize customer satisfaction. Determining the fulfillment levels of design requirements (DRs) and parts characteristics (PCs) is an important decision problem during QFD activity processes for new product development. Unlike the existing literature, which mainly focuses on the determination of DRs, this paper proposes fuzzy linear programming models to determine the fulfillment levels of PCs under the requirement to achieve the determined contribution levels of DRs for customer satisfaction. In addition, considering the design risk, this paper incorporates failure modes and effect analysis (FMEA) into QFD processes, which is treated as the constraint in the models. To cope with the vague nature of product development processes, fuzzy approaches are used for both FMEA and QFD. The illustration of the proposed models is performed with a numerical example to demonstrate the applicability in practice.     

Estimation of second-order properties from jittered time series

This paper considers spectral and autocovariance estimation for a zero-mean, band-limited, stationary process that has been sampled at time points jittered from a regular, equi-interval, sampling scheme. The case of interest is where the sampling scheme is near regular so that the jitter standard deviation is small compared to the sampling interval. Such situations occur with many time series collected in the physical sciences including, in particular, oceanographic profiles.Spectral estimation procedures are developed for the case of independent jitter and autocovariance estimation procedures for both independent and dependent jitter. These are typically modifications of general estimation procedures proposed elsewhere, but tailored to the particular jittered sampling scheme considered. The theoretical properties of these estimators are developed and their relative efficiencies compared.The properties of the jittered sampling point process are also developed. These lead to a better understanding, in this situation, of more general techniques available for processes sampled by stationary point processes.     

Modelling the Quality of Automatic Quality Checks

The paper addresses the problem of assessing the accuracy and utility of automatic quality tests used in high-speed production. A method is proposed for estimating the probabilities that the production process produces a product which is defective, that non-defective product will pass the test, and that a defective product fails the test. Data for printed circuit manufacture are used to demonstrate the method. Models of the effectiveness of various product testing procedures are investigated, the expected net profit is calculated and the probability of dispatching a defective product to a customer assessed.     

A new methodology for evaluating sustainable product design performance with two-stage network data envelopment analysis

Sustainable product design has been considered as one of the most important practices for achieving sustainability. To improve the environmental performances of a product through product design, however, a firm often needs to deal with some difficult technical trade-offs between traditional and environmental attributes which require new design concepts and engineering specifications. In this paper, we propose a novel use of the two-stage network Data Envelopment Analysis (DEA) to evaluate sustainable product design performances. We conceptualize “design efficiency” as a key measurement of design performance in terms of how well multiple product specifications and attributes are combined in a product design that leads to lower environmental impacts or better environmental performances. A two-stage network DEA model is developed for sustainable design performance evaluation with an “industrial design module” and a “bio design module.” To demonstrate the applications of our DEA-based methodology, we use data of key engineering specifications, product attributes, and emissions performances in the vehicle emissions testing database published by the US EPA to evaluate the sustainable design performances of different automobile manufacturers. Our test results show that sustainable design does not need to mean compromise between traditional and environmental attributes. Through addressing the interrelatedness of subsystems in product design, a firm can find the most efficient way to combine product specifications and attributes which leads to lower environmental impacts or better environmental performances. This paper contributes to the existing literature by developing a new research framework for evaluating sustainable design performances as well as by proposing an innovative application of the two-stage network DEA for finding the most eco-efficient way to achieve better environmental performances through product design.     

Joint determination of production quantity,inspection schedule,and quality control for an imperfect process with deteriorating products

In this paper, we study the simultaneous effects of both deteriorating product items and deteriorating production processes on economic production quantity, inspection schedules, and the economic design of control charts. Deterioration times for both product and process are assumed to follow arbitrary probability distributions. The product quality characteristic, however, is assumed to be normally distributed. Applications of the proposed model are demonstrated through illustrative examples.     

Economic design of inspection procedures using guard band when measurement errors are present

One of the most important aspects in designing production systems is implementing an adequate inspection procedure to ensure the product quality. Our literature study indicates that two important questions still remain unanswered. First, most of the previous studies on inspection procedures are mainly concerned with how to evaluate and analyze the adequacy of inspection procedures during a production stage. Although the issue of the adequacy of inspection procedures at this point is clearly important, many production processes may better benefit from designing enhanced inspection procedures during an early design stage. Second, the majority of previous studies do not incorporate possible economic impacts of measurement errors when inspection procedures need to be designed. More extensive efforts in designing inspection procedures need to be investigated based on economic considerations. Two approaches, the use of guard band and the selection of inspection precision level, are simultaneously examined for designing economic inspection procedures. By incorporating these two approaches, this paper proposes an optimization scheme for economic design of inspection procedures. A numerical example along with sensitivity analysis demonstrates the applicability of the proposed model.     

Spatial structuring and the development of number sense: A case study of young children working with blocks

This case study discusses an activity that makes up one of five lessons in an ongoing classroom teaching experiment. The goal of the teaching experiment is (a) to gain insight into kindergartners’ spatial structuring abilities, and (b) to design an educational setting that can support kindergartners in becoming aware of spatial structures and in learning to apply spatial structuring as a means to abbreviate and ultimately elucidate numerical procedures. This paper documents children's spatial structuring of three-dimensional block constructions and the teacher's role in guiding the children's learning processes. The episodes have contributed to developing the activity into a lesson that could foster children's use of spatial structure for determining the number of blocks. The observations complement existing research that relates spatial structuring to mathematical performance, with additional insight into the development of number sense of particularly young children in a regular classroom setting.