• The Journal of Society for e-Business Studies
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• v.17 no.3
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• pp.15-41
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• 2012

Recently, there happens many purchasing cases encouraged by friends' recommendation in SNS (Social Network Service). This study investigates the effect of friend recommendation on consumers' purchasing heuristic. For this purpose, we compare the effect of friend recommendation with consumer recommendation in terms of trustworthy, specialty, relevancy. Usually, the frequency of friend recommendation is far lower than that of consumer recommendation. Hence, we examine how the effect of information source (friend recommendation or consumer recommendation) is moderated by the frequency of recommendation, as well. As results, this study finds out that, under the same frequency, friend recommendation does not have significantly stronger effect on the purchasing heuristic, although friend recommendation is evidenced as one of significant heuristic inducers. However, in terms of trustworthy, friend recommendation is significantly superior to the consumer recommendation. Moreover, under sufficiently higher frequency, friend recommendation works as better heuristic factor than consumer recommendation. The results deliver managerial implications in the perspective of understanding consumers' purchasing decisions and responding strategies of firms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.159-167
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• 2009

In this paper, we consider a single-vendor single-buyer supply chain problem where a single vendor orders raw materials from its supplier, then using its manufacturing processes converts the raw materials to finished goods in order to deliver finished goods to a single buyer for effective implementation of Just-In-Time Purchasing. An integrated lot-splitting model of facilitating multiple shipments in small lots between buyer and supplier is developed in a JIT Purchasing environment. Also, an iterative heuristic solution procedure is developed to find the order quantity for finished goods and raw materials, and number of shipments between buyer and supplier. We show by numerical example that when the integrated policy is adopted by both vendor and buyer in a cooperative manner, both parties can benefit.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.69-80
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• 2023

Purpose: The purpose of this study is to identify factors that affect decision-making for e-commerce users and to present ecommerce companies with the company's strategic directions for consumer purchases. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between brand image, product liking, heuristic and purchase intention and the difference according to psychological power. For analysis a total of 212 valid questionnaires from e-commerce users were used. confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both brand image and product liking had a significant effect on purchase intention as well as heuristics. However, heuristics did not affect the purchase intention. It was found that the relationship between brand image, product liking, heuristic, and purchase intention differed depending on the psychological power. Conclusions: Companies should seek ways to increase the positive brand image and likability of products so that consumers can quickly purchase products. In the relationship between brand image and heuristic, the low-psychological group has more influence on heuristic, and in case of product liking, the high-psychological group has more influence on heuristic. In the relationship between brand image and product liking for purchase intention, both in the high psychological power group affect more influence on purchase intention. Since the process of purchasing products varies depending on the consumer psychological power tendency, it is necessary to identify the characteristics of consumers and establish strategies for purchasing promotion measures.

• IE interfaces
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• v.24 no.1
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• pp.51-57
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• 2011

The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In the last decade, TPP has received some attention of the researchers in the operational research area. However, all of the past researches for TPP are restricted on a single purchaser (vehicle). It could be the limitation to solve the real world problem. The purpose of this paper is to suggest the capacitated multiple TPP (CMTPP). It could be used in inbound logistics optimization in supply chain management area and many others. Since TPP is known as NP-hard, we also developed the heuristic algorithm to solve the CMTPP.

• Journal of Distribution Science
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• v.17 no.10
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• pp.73-81
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• 2019

Purpose - The purpose of this study was to examine the effect of the heuristic type of consumers affecting purchase decision making and the intention of shopping value in their relationship to derive mobile social commerce purchase promotion plans. Research design, data, and methodology - A research model was constructed to relate the mediating effect of shopping value between heuristic types and purchase intentions. A total of 233 valid questionnaires were used for analysis for users using mobile social commerce. The statistical program used SPSS 24.0 and AMOS 24.0, and correlation analysis, regression analysis, and 3-step parametric regression analysis were used for the analysis. Results - The results of the analysis showed that representativeness heuristics, availability heuristics, adjustment heuristics, and affect heuristics had a statistically significant effect on the utilitarian value and the hedonic value. On the other hand, affect heuristics among the heuristic types were found to have the greatest influence not only on the utilitarian value but also on the hedonic value. The two types of shopping value were found to be partially mediated between representativeness heuristics and purchase intentions, between adjustment heuristics and purchase intentions, and fully mediated between availability heuristics and purchase intentions, affect heuristics and purchase intentions. Conclusions - These findings suggest that mobile social commerce companies should check in advance how consumer heuristic types affect purchase intentions. In particular, affect heuristics are caused by consumers' emotional mood such as mood or external stimulus being more important to decision making than rational decision making. Therefore, the result of this study suggests that it can be an important factor to secure the competitiveness that the potential customers who access to use mobile social commerce can feel enough fun and enjoyment in the platform provided by the company. It is also worth paying attention to the utilitarian and hedonic values perceived by consumers. This is because the judgment regarding the economic, convenience and important information provided by the mobile social commerce users affects the purchase intention through the trust of the information, past use, and shopping experience displayed on the mobile social commerce platform.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.449-455
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• 2002

This paper considers that advanced planning and scheduling (APS) in manufacturing and the efficient purchasing where each customer order has its due date and multi-suppliers exit We present a Make-To­Order Supply Chan (MTOSC) model of efficient purchasing process from multi-suppliers and APS with outsourcing in a supply chain, which requires the absolute due date and minimized total cost. Our research has included two states. One is for efficient purchasing from suppliers: (a) selection of suppliers for required parts; (b) optimum part lead­time of selected suppliers. Supplier selection process has received considerable attention in the business­management literature. Determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions usually is complex and unstructured. These influence factors can be divided into quantitative and qualitative factors. In the first level, linguistic values are used to assess the ratings for the qualitative factors such as profitability, relationship closeness and quality. In the second level a MTOSC model determines the solutions (supplier selection and order quantity) by considering quantitative factors such as part unit price, supplier's lead-time, and storage cost, etc. The other is for APS: (a) selection of the best machine for each operation; (b) deciding sequence of operations; (c) picking out the operations to be outsourcing; and (d) minimizing makespan under the due date of each customer's order. To solve the model, a genetic algorithm (GA)-based heuristic approach is developed. From the numerical experiments, GA­based approach could efficiently solve the proposed model, and show the best process plan and schedule for all customers' orders.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.40-46
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• 2015

The modular assembly system can make it possible for the variety of products to be assembled in a short lead time. In this system, necessary components are assembled to optional components tailor to customers' orders. Budget for inventory investments composed of inventory and purchasing costs are practically limited and the purchasing cost is often paid when an order is arrived. Service cost is assumed to be proportional to service level and it is included in budget constraint. We develop a heuristic procedure to find a good solution for a continuous review inventory system of the modular assembly system with a budget constraint. A regression analysis using a quadratic function based on the exponential function is applied to the cumulative density function of a normal distribution. With the regression result, an efficient heuristics is proposed by using an approximation for some complex functions that are composed of exponential functions only. A simple problem is introduced to illustrate the proposed heuristics.

• The Journal of Information Systems
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• v.26 no.4
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• pp.107-135
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• 2017

Purpose Along with the growth of smart phones and social networking service (SNS), social commerce continues to expand. Although online reviews have become an important source of the information that consumers use to make purchasing decisions, theoretical development and empirical testing in this area are still limited. Thus, there is a need to develop further understanding about the influence of electronic word-of-mouth (eWOM). Drawing upon the heuristic - systematic model (HSM) which is one of the dual-process theories, this study develops a research model that explains key factors influencing consumers' eWOM credibility. Furthermore, this study verifies that consumer's eWOM credibility is a key determinant of eWOM and purchase intentions. Design/methodology/approach The proposed model is empirically tested with 493 users who have experience in WeChat-based social commerce. The structural equation model (SEM) analysis is used to evaluate the research model and hypotheses. Findings The major findings are as follows. First, argument quality of eWOM (a systematic factor) has a positive effect on eWOM credibility. Second, source credibility and recommendation consistency of eWOM (heuristic factors) are positively associated with eWOM credibility. Finally, purchase and eWOM intentions greatly depend on eWOM credibility. These results confirm the effectiveness of HSM in explaining eWOM mechanisms in SNS-based social commerce. The details of findings and implications are presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.47-65
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• 1998

We consider a multiperiod capacity planning problem for determining a mix of flexible and dedicated capacities under budget restriction. These capacities are controlled by purchasing flexible machines and/or new dedicated machines and disposing old dedicated machines. Acquisition and replacement schedules are determined and operations are assigned to the flexible or dedicated machines for the objective of minimizing the sum of discounted costs of acquisition and operation of flexible machines, new dedicated machines, and old dedicated machines. In this research, the Problem is formulated as a mixed integer linear Program and solved by a Lagrangian relaxation approach. A subgradient optimization method is employed to obtain lower bounds and a multiplier adjustment method is devised to improve the bounds. We develop a linear programming based Lagrangian heuristic algorithm to find a good feasible solution of the original problem. Results of tests on randomly generated test problems show that the algorithm gives relatively good solutions in a reasonable amount of computation time.