The rapid pace of e-commerce development has resulted in several manufacturers selling their products online to stay competitive and increase accessibility to their products. This paper investigates the effect of adopting a dual-channel (comprised of a traditional retail channel and a direct online channel) on the performance of a two-level supply chain (manufacturer-retailer). Through this strategy, the manufacturer would like to offer customized products through a direct online channel (i.e. make-to-order), in addition to offering its standard product through the traditional retail channel (i.e. make-to-stock). The objective is to maximize the total profit of the system when this strategy is adopted. A linear demand function is used for both channels in which the demand depends on the selling prices (markup margin), the quoted delivery lead-time, and product differentiation. This investigation is compared to a benchmark scenario, where the supply chain is comprised of a single-channel strategy (retail channel only) where one type of product is offered; the standard product. In both strategies, the paper analyzes the change in the profit, markup margin and the inventory decisions that result from adopting the dual-channel strategy. The findings of this paper demonstrate that adding a customized-product online channel would increase the profit of the centralized supply chain system. However, it created a conflict due to competition between the retail and online channels. A numerical example and sensitivity analysis have been used to demonstrate this effect and to draw specific managerial insights
Purpose Studies have suggested that attributes are dynamic and a life cycle of product and service attributes exists. When an innovative feature is introduced, the feature might attract and delight customers. However, with the passage of time the state of the attractiveness of this feature may change, for better or for worse. The purpose of this paper is to provide a detailed model that shows the factors and related sub-factors that affect the life cycle of a feature and thereby explain the changes that may happen to a feature over time. Design/methodology/approach This model provide detailed explanations of the direct and indirect factors that affect the states of a feature, the ones that affect the rate of adoption, and the ones that trigger the changes between states. The model uses a current-market product’s feature to discuss the effects of these factors on the life cycle of this feature in detail. Findings This paper extends the theory of attractive quality attributes by identified seven states of the feature in its life cycle. These states are as follows: unknown/unimportant state, honey pot state, racing state, required state, standard state, core state, and dead state. This paper also identified eight major factors that affect the transition of the feature from one state to another. These factors include demographic, socioeconomic, behavioural, psychological, geographical, environmental, organisational, and technological factors. Originality/value The findings of this paper provide additional evidence that product and service attributes are dynamic. This paper also increases the validity of the attractive quality attributes theory and the factors that affect the state of the feature in its life cycle. The understanding of the state of the feature in its life cycle, and the factors that influence this change, helps not only in the introduction of completely new features but also in knowing when to remove obsolescent ones.
Internet-based technologies have changed the way firms do business and manage their supply chains. They have influenced customers’ purchase patterns, thereby motivating manufacturers to introduce online channels alongside traditional ones. Such structures are known as dual-channels. Nowadays, an increasing number of manufacturers offer a return policy to attract more customers and to stay competitive. Furthermore, learning-based continuous improvements help firms cope with market changes and be competitive, flexible and efficient. This thesis presents three main models: The first model investigates the effect of adopting a dual-channel (comprised of a retail channel and an online channel) on the performance of a two-level (vendor-retailer) supply chain. The objective is to maximize the total profit of the system by finding the optimal markup margin and inventory decisions before and after adopting the dual-channel. The results show that adding an online channel would increase the profit of the system. However, it creates a conflict due to competition between the retail and online channels. The second model studies a supply chain system, which is comprised of production, refurbishing, collection, and waste disposal processes. A return policy in which customers can return the purchased item for a refund is also considered. The purpose is to examine the effect of different return policies on the behavior of the system before and after adopting the dual-channel strategy. In both strategies, the model analyzes the change in the profit, the pricing and inventory decisions. The findings demonstrate that the more generous the return policy is, the higher the demand, the selling prices and the overall profit. The third model investigates the effects of learning and forgetting in the vendor’s production processes. It also considers single- and dual-channel strategies. Each channel structure can adopt any of six inventory policies. Learning and forgetting effects are considered in all policies except one. The objective is to maximize the profit of the system by finding the joint optimal pricing and inventory decisions. The results suggests that learning, despite being impeded by forgetting, reduces inventory-related costs thereby allowing the chain to reduce the prices of its product(s), which increases demand and subsequently sales.
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