With the rapid development and widespread adoption of digital technology, two-sided platforms increasingly leverage digital technology to enhance operations and facilitate transactions. However, varying levels of acceptance among consumers and providers present platforms with three strategic options for technology adoption: no adoption, partial adoption, or full adoption. Although previous studies have explored technology adoption decisions in two-sided platforms, there remains a research gap in the choice between partial and full technology adoption. This paper aims to address this gap by developing a game-theoretic model to analyze the impact of different technology adoption strategies on two-sided platforms, consumers, and providers. Our findings reveal that the adoption of digital technology can increase both service supply and demand but decrease service prices and commission rates. Notably, in the scenario of partial technology adoption, the price of traditional services is higher than when technology is not adopted. Moreover, we demonstrate that higher operating costs do not necessarily incentivize the platform to adopt digital technology. Specifically, platforms are more likely to partially adopt technology when operating costs are low and fully adopt it when costs are moderate. Furthermore, we find that partial technology adoption can generate more consumer and provider surplus but may reduce overall social welfare. Our study provides strategic guidance for platform managers regarding adopting digital technology within their operations management.

Artificial intelligence (AI)-enabled live-streaming is rapidly transforming online retailing, while also introducing significant operational challenges related to post-purchase dissatisfaction and consumer distrust toward AI streamers. We develop a Stackelberg game to analyze a dual-channel supply chain in which a manufacturer sells through an offline channel and a platform-based live-streaming channel operated under either an agency mode or a reseller mode. The model formalises the key operational trade-offs in streamer selection: the human streamer typically provides stronger selling influence but may induce impulsive purchasing and higher product returns, while the AI streamer mitigates return risk but suffers a trust deficit that can be alleviated by investing in intelligence levels. Our analysis reveals that the optimal streamer choice is contingent upon the product's post-purchase expectation mismatch probability and the human streamer's unit sales cost. Specifically, the human streamer is preferred for low-return categories to maximise conversion, while the AI streamer is optimal for high-return products to curb impulsive buying. The reseller mode emerges as a Pareto-dominant strategy for managing products characterised by high return risks. Two extensions, which consider a positive post-purchase expectation mismatch probability and channel advantage heterogeneity, confirm the robustness of our main insights.

As a major instrument of quality assurance implemented in online business, quality certifications play pivotal roles in retailing platforms’ operations. This paper studies whether retail platforms can improve the product quality of sellers (manufacturers) through implementing quality certifications. We develop a game-theoretic model which consists of one retail platform and two competing manufacturers with differentiated brand positioning. Considering the platform can flexibly set the quality standard, we explore the quality certification for the platform where the quality and price decisions of the heterogeneous manufacturers can be affected. We find that the certification is profitable (unprofitable) for platform when the certification cost coefficient is low (high). Additionally, we identify two effects of the consumer preference on the certification: the low-preference effect and the high-preference effect, which have opposing impacts on the standard and the quality investment of certified manufacturers. Interestingly, smaller differences in brand positioning enhance the high-preference effect, which reflects the complementary role of the high-preference effect in expanding product vertical differentiation. Moreover, when implementing the certification, the platform may prefer to encourage only the high-end manufacturer to participate in the certification, as the different impacts of two preference effects render certification unprofitable for the low-end manufacturer. More interestingly, we find that the introduction of quality certification has a two-fold effect. It incentivizes participant (non-participant) to enhance (degrade) its product quality and price. Thus, the certification expands the vertical differentiation of the products on the platform.

To improve patients' welfare, governments can regulate the availability of the low-price drugs (LPDs) through lower wholesale purchasing or retail selling of the LPD. This paper characterizes two common constrained policies from the practices of pharmaceutical markets. The first (policy P) controls the ratios of the LPD's purchasing quantity and fee. The second (policy S) controls the ratios of the LPD's selling quantity and revenue. Considering a pharmaceutical supply chain consisting of two independent manufacturers and a hospital, we investigate the impacts of two policies on the LPD's availability and the whole industry gains. Our results show that policy P dominates policy S in two aspects: (a) policy P provides a higher product availability of the LPD and (b) policy P reduces less profits for the pharmaceutical supply chain. Specifically, policy P could incur a win-win outcome for the patient and the supply chain. We further show that the demand allocation of the LPD, the substitution degree, and the profit margins' difference can significantly affect the performances of the policies.

After decades of outsourcing to low-cost countries, companies are restructuring their production footprint globally. Especially having experienced supply chain disruption caused by the unprecedented Covid-19 pandemic for the past several years, many multinational companies are considering bringing their operations back home (i.e., reshoring). At the same time, the U.S. government proposes using tax penalties to motivate companies to reshore. In this paper, we study how a global supply chain adjusts its offshoring and reshoring production decisions under two different circumstances: (1) under traditional corporate tax regulations; (2) under the proposed tax penalty regulations. We analyze cost variants, tax structures, market access and production risks to identify conditions where global companies decide to bring manufacturing back to their domestic countries. Our results show that multinational companies would be more likely to relocate the production from the main foreign country to an alternative country that enjoys even lower production costs under the proposed tax penalty. As identified by our analysis and as well as numerical simulations, reshoring can only occur in rare situations such as when the production costs in the foreign countries are close to that in the domestic country. Besides potential national tax reform, we also discuss the impact of the Global Minimum Tax Rate proposed by the G7 on global companies' offshoring/reshoring decisions.

Gray markets, a double‐edged sword for the multinational firms' profitability, can boost the sales revenues of low‐end subsidiaries while cannibalizing the demands of high‐end arms. To counter the adverse effects of the gray market, firms can flexibly adjust between the two strategies of setting prices (the price strategy) and choosing quantity (the quantity strategy) for its products. This paper investigates the best strategy for responding to gray markets. We consider a firm that produces two substitute products, each sold in an independent market (country). A gray marketer purchases the product sold in the low‐priced market and resells it in the high‐priced market, thereby starting a gray market. By studying the conditions of determining when and which strategy is more profitable, we establish several findings that are absent in the current literature. For instance, we find that it is likely that the quantity strategy could also be the best one in the presence of the gray competition. Moreover, implementing the quantity strategy can even automatically eliminate the gray market, which will not happen if the price strategy is employed. In addition, we identify special cases in which implementing one of the two strategies can lead to profit improvements while employing the other will cause the firm to suffer in case a gray market exists. We also examine the robustness of these findings in several cases of extensions of our model.

In practice, manufacturers may encroach on retail markets through a variety of methods, one being through the use of an online channel direct to the consumers, called encroachment. Current research typically assumes that downstream retailers retain procurement from the encroaching supplier. In reality, however, retailers may have the option of switching suppliers after encroachment. By considering a supply chain consisting of one manufacturer and one retailer with outside options, this paper analyzes the effects of the option of switching suppliers on the supply chain players' strategic interactions under the threat of supplier encroachment. We consider that the manufacturer makes encroachment decision preceding the retailer's switch decision. We capture various outcomes of the encroachment and switch decisions by using a classic encroachment model with quantity decisions (Cournot model). Specifically, we identify two effects of the outside option on the strategic encroachment decision. The first, the deterrence effect, means that the manufacturer's encroachment is deterred by the threat of switching supplies altogether; while the second, the permissive effect, indicates that the retailer intends to switch to the alternative source after the encroachment. Interestingly, we show that the encroachment could improve the total profit of the incumbent manufacturer and the retailer even when the retailer's switch has occurred. In this case, however, the manufacturer profits while the retailer is hurt by the encroachment and the switch. Finally, we also investigate several extended cases to demonstrate the robustness of our findings.

Digital music albums can be sold either as singles or as a full album, which is not an option for selling physical music products. This paper investigates three pricing strategies for selling digital music albums. The first (strategy S) sets a unified unit price and all songs are sold at this price. The second (strategy F) determines a bundling price for selling the whole album. The third (strategy M) mixes strategies S and F. It offers two prices: one is for a unit song and the other for the whole album. We develop mathematical models for this problem and design enumeration-based iteration algorithms to solve these models for optimality. Through a database consisting of 243 groups of numerical results, we establish a decision tree model, a popular data mining technique, to explain which strategy should be employed under various conditions.

Business practices have demonstrated that a contract manufacturer (CM) can introduce an own-label product and thus compete with its original equipment manufacturer (OEM), i.e., factory encroachment, which has not been obtained much attention in literature. Considering a three-level outsourced supply chain consisting of a CM, an OEM, and a retailer, this paper analyzes the impact of factory encroachment on players' gains. We show that factory encroachment could implement Pareto improvement, i.e., all supply-chain players' gains increase under encroachment. We also demonstrate that factory encroachment always offers more surplus to the entire supply chain and the consumer. In addition, the most preferred channel for the supply-chain players, the entire supply-chain system, and the consumer are investigated. We find that an encroachment strategy could be simultaneously favored by all involved parties, provided there is no integration between the OEM and the retailer. However, if the OEM and the retailer act as a single entity, only the no-encroachment strategy could be favored by all parties simultaneously.

Many small and medium-sized enterprises (SMEs) have built web presence, but few have advanced further to embrace the Internet as an online direct sales channel (ODSC). This study proposes and empirically tests a research model on the role of two risk constructs--perceived risk and risk propensity-in the adoption and continued use of ODSC among SMEs. The results show that the roles of the two risk constructs differ substantially: risk propensity has a direct and an indirect effect, but perceived risk only has an indirect effect, on SMEs' intention to use ODSC. Furthermore, the impacts of the two risk constructs differ in the two temporal stages--the adoption and continued use--of ODSC. The findings of the study validate behavioral decision theories from a risk perspective that non-rational (i.e., risk propensity) as well as rational factors (i.e., perceived risk and perceived business value) shapes organizational decision-making.

Inventory pre-positioning is critical to quickly and efficiently responding to potential disasters. This paper considers a NPO (a relief agent) that requires stockpiling multiple products for responding multiple potential disaster events. By employing the multi-product newsvendor (MPNV) approach, this paper establishes a multiple relief materials’ storage model that aims to minimise the expected total cost of the NPO. Our model acknowledges that the occurrence of a disaster, the demand after a disaster and the donation after a disaster are uncertain. Given the no-budget constraint, this paper shows the implicit conditions that determine the optimal solutions; for the case with a budget constraint, the paper develops a two-binary iterative approach to solve the model with a budget constraint. Numerical examples are conducted to investigate the impacts of model parameters. The paper further proposes a flexible storage policy, in which the NPO and the supplier jointly stockpile relief materials. The optimal solution of the case with the flexible stockpiling policy is also characterised. Moreover, this paper shows the policy implementation can simultaneously increase the performance of the NPO and the supplier; and both players of the supply chain prefer that the supplier solely holds all inventory.

Since the decision of non-price feature such as product quality draws a little attention in the literature of dual-channel supply chains, this paper investigates price and quality decisions in dual-channel supply chains, in which a single product is delivered through a retail channel, a direct channel, or a dual channel with both retail and direct channels. Considering the supply chains can be centralized or decentralized, we demonstrate that quality improvement can be realized when a new channel is introduced. Moreover, we employ two themes in terms of channel-adding Pareto zone to characterize the impacts of channel structures on supply-chain performance, including the whole system's profit (for the centralized system), each player's profit (for the decentralized system), and consumer surplus. When price and quality decisions are considered, we find the supply chain performance could be improved due to a new channel augmented. Moreover, we show the effects of the quality sensitivity parameters of different channels on price and product quality, as well as profits and consumer surplus. (C) 2016 Elsevier B.V. All rights reserved.

Developing an efficient policy to determine the inventory a non-profit organization (NPO) should stockpile to respond to potential disasters plays a vital role in humanitarian relief. Incorporating social donation and emergency spot purchasing, this paper develops a (generalized) two-stage delivery process model to characterize relief materials’ delivery after a disaster. We propose an analytical model that aims to minimize the total costs when all demands incurred by an unexpected disaster need to be fully satisfied. Moreover, we determine that the optimal solution uniquely exists and characterize the effects of key parameters. Last, this paper also develops a risk-sharing scheme, in which the NPO and the supplier jointly stockpile relief materials. Under some mild conditions, we show that implementing the scheme could increase the storage quantity and decrease the total costs simultaneously. Several numerical examples are employed to validate the model, as well as the value of the proposed risk-sharing scheme.

A fresh agricultural food online exchange system is gradually becoming an emerging e-business model in China. However, how and when to make an investment in this new business model is risky due to the unique characteristics of fresh agricultural food. In this paper, from a third party decision maker’s perspective, we propose an evolutionary discounted cash flow model to investigate the optimum time point for investment. Based on the assumptions of base demand, the derived e-demand occurring on the pendent e-business system can be characterized by non-stationary stochastic processes. Then our new model can further be innovatively analyzed by considering the dynamic scheme of the cash flow and its evolution. The analytical results suggest the optimal investment time point depends upon the consumers’ switch rate from the physical store to e-store and on the urbanization rate. A Monte Carlo simulation is further presented to compare the effects of multiple uncertainties embedded into the system. Our uncertainty analysis reveals that when government financial support fluctuates greatly, the optimal investment time could be either in the very beginning or in the end. This optimal time strategy also holds for the random demand factor after the coefficient variation of the demand reaches a certain threshold.

B2B e-commerce has fundamentally changed the way in which an organization purchases goods/service. Nowadays, the adoption of e-procurement, which means the electronic acquisition of goods/service, has been prevalent in supply chain management. A variety of supplier selection models have been developed in supply chain management literature. In this research, an adaptive supplier selection mechanism is proposed to help buyers evaluate suppliers in an e-marketplace. A Multi-Agent System simulation package of Repast is used to create a realistic environment where different kinds of suppliers and buyers equipped with the proposed selection model can interact so as to study the performance of the proposed selection model. We evaluate three supplier selection models and find that our proposed model outperforms the other two in terms of robustness and performance.

A component supplier holding patents can calculate the intellectual property licensing fees either as a percentage of sales prices of its customer manufacturers' products (i.e., product-based strategy) or as a percentage of the wholesale price of its component (i.e., component-based strategy). Selecting which strategy to license the patent plays a vital role in supply-chain players' strategic interactions, especially when the downstream manufacturers compete. This paper investigates which strategy is favored more by players of a supply chain, which consists of a component supplier and two duopoly manufacturers. The manufacturers are assumed to be heterogeneous in production cost but produce and competitively sell homogenous goods. Employing a supplier Stackelberg game model, we demonstrate that the component supplier prefers to implement the product-based strategy; nevertheless, the manufacturers' preferences are dependent on how effectively they produce products. Specifically, the product-based strategy could be favored by the manufacturer with a sufficiently high cost advantage over the rival. Furthermore, we find that the supply-chain players' preferences of licensing strategy could be dependent on factors such as the market size, the differences of the production costs, and unit royalty fees when the products are imperfect substitutes.

Based on the resource‐based view (RBV) and the transaction cost economics (TCE) theories, we study the impact of IT capability on the performance of port supply chain using an IT‐enabled transaction cost frontier model where the IT capability is modeled as a unique production input and as an endogenous transaction attribute as well. By examining the optimal levels of IT capability for different port systems from the viewpoint of production cost and transaction cost, we find theoretical evidence to explain why a port system with a horizontal competitive governance mode is less successful at integrating a port IT system in practice. Moreover, we find that the optimal IT capability of an individual port operator is lower than the IT capability in an integrated heterogeneous system. We further investigate how to improve IT capability to the desired system level through different forms of an incentive system that includes a subsidy offered by the port authority to coordinate the entire port system. The fixed subsidy is found to be the most cost‐effective and the easiest to implement. In addition, considering that information about effort cost for IT capability can be private under a market or hybrid governance mode, we study the performance of a direct revelation mechanism when revealing the port operator's private information and true cost to the port authority.

With the overwhelming findings that systemic risk dominates idiosyncratic risk in individual firms along a supply chain or in an industrial sector, and noting the fact that supply chain literature so far has been firm-based, it is critical to analyse inter-firm transactions and related risks which have largely been omitted from current supply chain research. To advance along this critical dimension, we develop a transaction cost frontier model that allows inter-firm transaction facilities in terms of a port-focal supply chain modelling framework. The key findings are as follows. (1) Environment heterogeneity is a characteristic transaction attribute, and logistics efficiency is critically dependent on both intra-firm asset specificity (Williamson, 2002) and inter-firm environment heterogeneity when ports are considered as transaction facilities. Port logistics demonstrates that horizontal integration (as opposed to vertical integration) becomes more cost effective as environment heterogeneity increases, given the same degree of asset specificity among individual ports. (2) An adaptive advantage (eg, transaction efficiency) is identified and characterized through the port-focal industrialization of supply chains, and is found to be an explanatory cause for the geographically concentrated horizontal specialization and differentiation, as increasingly observed in practice. Logistics industrialization will bring about the growth of port-focal urbanization.

ABSTRACT The classic newsvendor model was developed under the assumption that period‐to‐period demand is independent over time. In real‐life applications, the notion of independent demand is often challenged. In this article, we examine the newsvendor model in the presence of correlated demands. Specifically under a stationary AR(1) demand, we study the performance of the traditional newsvendor implementation versus a dynamic forecast‐based implementation. We demonstrate theoretically that implementing a minimum mean square error (MSE) forecast model will always have improved performance relative to the traditional implementation in terms of cost savings. In light of the widespread usage of all‐purpose models like the moving‐average method and exponential smoothing method, we compare the performance of these popular alternative forecasting methods against both the MSE‐optimal implementation and the traditional newsvendor implementation. If only alternative forecasting methods are being considered, we find that under certain conditions it is best to ignore the correlation and opt out of forecasting and to simply implement the traditional newsvendor model.

This article develops and empirically tests a research framework that models the role of technological, organizational, and environmental factors in organizational intention toward using e-procurement systems. The partial least square analysis of survey data from 211 firms in China demonstrates that technological factors including perceived efficiency benefits and perceived ease, organizational factors including business to business commerce expertise, information sharing culture, and top management support, and an environmental factor, business partner pressure, shape in different ways organizational intention to adopt and to continue with e-procurement. The findings of the study not only offer valuable insights for stimulating the diffusion of e-procurement systems but also provide important guidance to systems vendors in strategizing their marketing campaigns and focusing limited resources on relevant strategic components.