Sales of accessories and add-ons are strategically important as profit centers for manufacturers of consumer products. In such situations, a durable product with too many attributes might reduce the chance of selling optional items that increase the functionality of the product, whereas too few product attributes will make the product less attractive, thereby reducing profitability. Hence, determining the optimal amount of add-on functionality of a durable product is critical in product design. Another retail challenge is how to sell a durable product and along optional add-on functionalities, whether they should be sold together or separately. This paper examines the number of attributes that a durable product should have by comparing three sales strategies: selling the durable product only (i.e., a one-product-fits-all strategy), selling the durable product and optional items simultaneously, and selling them separately. We compare the optimal level of product functionality among these three sales strategies considering three managerial goals: coverage of the target market, revenue maximization, and profit maximization. We also study the effect of consumers' desire for a product with over-specification in the optimal design. We determine that the sale of add-ons affects the optimal functionality of a durable product and how separately selling optional items can alleviate the tendency toward over-specification in product design.

When institutional investors trade large amounts of stock in the market, the tradingamount might impact the price, and this price change is called market impact (MI hereafter). Inaddition, their trading is always exposed to uncertain price change, and this is called timing risk. Such investors need to quantitatively evaluate the MI and timing risk, and decide the optimal execution strategy when considering the trade-off between them. Several previous studies assume temporary/permanent MI, while some recent studies discuss transient MI. On the contrary, most investors need to manage their downside risk when executing an order to meet the trading needs below a target cost. In this study, we discuss dynamic optimization models with transient MI and downside risk in order to decide the optimal execution strategy. Specifically, we propose the following three types of models based on Takenobu and Hibiki (2016) who assume temporary/permanent MI.

(1) Multiperiod model with step function using Monte Carlo simulation (Step model);

(2) Multiperiod model with piecewise linear (PwL) function based on the Step model; and

(3) One-period iterative model with static execution strategy (Iterative model).

We solve the optimal execution problems using these models, and conduct a sensitivity analysis to examine the benefits of the models. In addition, we compare the three models, and evaluate their characteristics and differences. We estimate the MI function and other parameters using market data, and derive the optimal execution strategies for practical use.

This paper presents the theoretical and practical investigations of a new method for prioritizing customer requirements (CRs) in the quality function deployment (QFD) process to improve the service quality of a communication system for disabled individuals. The theoretical contribution of this study is the development of a fuzzy analytic hierarchy process (fuzzy-AHP) with voting during QFD, which is based on fuzzy-set theory, the analytic hierarchy process, and linguistic voting. Fuzzy-set theory is crucial in addressing the ambiguity of linguistic terms used and judgments made by disabled people. The AHP is necessary to calculate the CR weights. A linguistic voting technique was integrated into fuzzy-AHP to consider not only the expert evaluations, but also the users' opinions on the CRs. The hybrid method proposed has the advantage of being able to be compared with existing methods in the sense that the opinions of real users are directly reflected on the CR weights in the QFD. The practical contribution of this paper is a case study on the design of an augmentative and alternative communication (AAC) system for individuals with a language disorder like aphasia. This case study was conducted to demonstrate the effectiveness of the method proposed. In the case study, 49 individuals with aphasia participated in the voting process. This is the first study to analyze the opinion data of such a large number of individuals with aphasia in the design of AAC systems. The effects of the voting technique on the CR weight are discussed by comparing the CR rankings of the method proposed with those of existing methods. The method proposed had a considerable influence on the target values of the technical characteristics used as input data in the second stage of QFD. This could lead to improving the service quality of communication systems designed for individuals with aphasia.

This paper focuses on the development of a work analysis support system for distribution processing and presents a case study of work analysis at a retail clothing order fulfillment center. The system comprises ultrasonic sensors for measuring a worker's ow line and a smartphone for measuring the worker's dominant hand acceleration. Models for estimating the worker's motion were derived from the data obtained. Candidate estimation models were the statistical models linear discriminant function, decision tree, and k-nearest neighbor algorithm, and we used generalization error by cross-validation as an index for choosing the optimal estimation model. The system was applied to the example of analyzing order picking in a clothing distribution center. The κ coefficient obtained indicated the degree of matching between the results of video analysis and tracking by our system to be 0.6 or more, which conffiermed the validity of our system.