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The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.

This study investigates the impact and economic viability of energy-efficient building envelope and orientation for contributing net zero energy building (NZEB) and suggests optimum thermal insulation thickness, optimum wall thickness, appropriate orientation and glazing types of window in the contexts of unique Bangladeshi subtropical monsoon climate.

The whole study was conducted through energy simulation perspective of an existing office building using building information modeling (BIM) and building energy modeling (BEM) tools which are Autodesk Revit 2017, Autodesk Green Building Studio (GBS) and eQUEST. Numerous simulation patterns were created for energy simulation considering building envelope parameters and orientations. A comprehensive data analysis of simulation results was conducted to sort out efficient passive design strategies.

The optimum thermal mass and thermal insulation thickness are 6.5 and 0.5 inches, respectively, considering energy performance and economic viability. This study highly recommends that a building should be designed with a small window-to-wall ratio in the south and west face. The window should be constructed with double glazing Low-E materials to reduce solar heat gain. The studied building saves 9.14% annual energy consumption by incorporating the suggested passive design strategies of this study.

The output of this work can add some new energy-efficient design strategies to Bangladesh National Building Code (BNBC) because BNBC has not suggested any codes or regulations regarding energy-efficient passive design strategies. It will also be useful to designers of Bangladesh and other countries with similar subtropical climatic contexts which are located in Southeast Asia and Northern Hemisphere of Earth.

This paper aims to simultaneously consider an inventory model with price and advertisement dependent demand, non-instantaneous deterioration rate with preservation technology investment, partially backlogged shortages and trade credit.

This model considered a non-instantaneous deterioration, which starts after a certain storage period with a constant rate. The proposed model focused on two things. The first one is to reduce the deterioration rate by preservation technology investment, and the second one is using an appropriate trade credit period to maximize the total profit. The classical optimization technique is used to solve the problem.

The authors found that trade credit, advertising cost, preservation technology affect the total cost and selling price is one of the most important decision variables affecting the model.

This study provides a reference for a manufacturer and a retailer on making inventory decisions under different pricing, advertisement expense, preservation technology investment and credit strategies. Four cases are presented to illustrate the inventory model. Sensitivity analyses are performed to gain managerial insights for decision-making.

The study simultaneously considers a non-instantaneous deterioration inventory model, trade-credit, and preservation technology and advertisement policy. From our literature search, no researcher has undergone this type of study.

Application of appropriate shading device strategies in buildings can reduce direct solar heat gain through windows as well as optimize cooling and artificial lighting load. This study investigates the impact of common shading devices such as overhangs, fins, horizontal blinds, vertical blinds and drapes on energy consumption of an office building and suggests energy efficient shading device strategies in the contexts of unique Bangladeshi subtropical monsoon climate.

This research was performed through the energy simulation perspective of a prototype office building using a validated building energy simulation tool eQUEST. Around 100 simulation patterns were created considering various types of shading devices and building orientations. The simulation results were analysed comprehensively to find out energy-efficient shading device strategies.

Optimum overhang and fin height is equal to half of the window height in the context of the subtropical climate of Bangladesh. South and West are the most vulnerable orientations, and application of shading devices on these two orientations shows the highest reduction of cooling load and the lowest increment of lighting load. An existing building was able to save approximately 7.05% annual energy consumption by applying the shading device strategies that were suggested by this study.

The shading device strategies of this study can be incorporated into the Bangladesh National Building Code (BNBC) as new energy-efficient building design strategies because the BNBC does not have any codes or regulations regarding energy-efficient shading device. It can also be used as energy-efficient shading device strategies to other Southeast Asian countries with similar climatic contexts of Bangladesh.

The advancement of technology opens many opportunities for retailing businesses to increase their profit through innovative strategies, such as discount offers, preorder programs and online payment services. The purpose of this study is to investigate decision-making methods for retailers who sell deteriorating products that utilize an e-commerce platform and offering preorder.

The authors study the optimum price and replenishment cycle when multiple discounts policy is implemented for customers when they purchase during the preorder period and make the payment via an online system. The proposed economic order quantity model works for noninstantaneous deteriorating items that will maximize the total profit. Moreover, it considers the effect of selling price and advertisement on customer demand. The concavity of the profit function is proved. Then, a comparison is carried out between the traditional payment system and online payment. Finally, two numerical examples and the sensitivity analysis are performed.

The results show the benefit of the system with online payment compared to the traditional one. Further analysis shows that the total profit increases when the frequency of advertisement, interest from the banking company, location perimeter and the nondeterioration time increase.

The proposed model guides e-commerce retailers optimizing the price and inventory decision when they offer a discount, preorder program and online payment service. No researcher has undergone a study with this complexity.

External factors such as improper handling, extreme weather and insect attacks affect product quality. It is most obvious in fruit products which have a high deterioration rate. Moreover, decaying fruits will increase the deteriorating of other good ones. The purpose of this study is to derive the optimal pricing and replenishment decisions for agricultural products considering the effect of external factors that induce deterioration.

In this paper, the study investigates ways to reduce the product deterioration rate by separating the near defective items from the other good products and accelerating the quick sales of the near defective items at a discounted price. The objective is to maximize the total profit by optimizing the selling price and the replenishment cycles. Two scenarios are investigated. In the first scenario, the retailer offers a selling price discount for near defective products to stimulate customer demand. In the second scenario, the retailer does not offer such discounts.

An algorithm to solve the model is derived. Further, numerical examples are developed to compare the total profit for the two scenarios. Theoretical derivations and graphical results show the concavity of the profit function. Finally, the sensitivity analysis shows that the total profit of the discount model is higher.

This study contributes to a new pricing and inventory decision model. The research provides insights to retailers on making optimal pricing and replenishment decisions for non-instantaneous deterioration items, as well as reducing the external factors that influence higher deterioration rate through separating good products from the near defective ones which are sold at a discount to induce the sale.

Artificial intelligence (AI) is shifting the way of how customers interact with organisations by blending both physical and digital environments, thereby creating a new paradigm of customer-organisation relationship. The new relationship boundary driven by AI principally challenges as well as creates opportunities for relationship marketing theories and practices. The main objective of this chapter is to present a framework named ‘physical-digital space’ to demonstrate how AI can merge the physical and digital world. To broaden the understanding, this chapter uses the lens of customer experience in relationship marketing. The framework extends the existing understanding and provides managerial implications on how an organisation can develop strategies so that a customer consciously or subconsciously develops a positive relationship with the organisation.

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.