Outsourcing Cost Research Articles

Business commonality, standardization and product cycles

By analyzing production with a continuum of tasks subject to common stochastic effects, the analysis shows that tension between business commonality and standardization is an important source of product cycles. The paper addresses the question of whether business commonality and standardization work in tandem or against each other in a general framework, when fragmentation of production is or is not possible due to contractual incompleteness or technology features. Unlike current literature, the analysis shows that a product cycle can be obtained even with complete contracts. This is so because retaining manufacturing within the firm enhances and exploits commonality in the early stages of production and, hence, reduces the moral hazard cost of providing incentives, which would be a hidden cost of outsourcing instead. Standardization later on can favor offshoring.

A Comparative Study of the Effect of Different Carbon-Reduction Policies on Outsourcing Remanufacturing.

To facilitate the green transformation of enterprises and realize low-carbon development, governments have adopted the policies of carbon emission constraint and carbon trade to promote enterprises’ low-carbon production. Although the two policies aim to reduce carbon emissions, they have different effects on enterprises’ production. Meanwhile, the development of remanufacturing caters to the low-carbon economy. Therefore, this article establishes the game models between an original equipment manufacturer (OEM) and a remanufacturer under carbon-emission-constraint and carbon-trade policies, analyzing the production decisions of enterprises under different policies to compare the influence of the two policies on outsourcing remanufacturing. The main conclusions of the article are as follows: (1) Both carbon-emission-constraint and carbon-trade policies increase the unit retail price of remanufactured and new products, reducing the new products sales volume. However, the sales volume of remanufactured products only decreases if the discount rate is less than the rate of carbon emissions of the two products. (2) The upper limit of carbon emissions can affect the unit outsourcing cost. The unit cost of outsourcing under the carbon-emission-constraint policy is only higher when the upper limit of carbon emissions is less than a certain threshold, and the discount rate is larger than the proportion of carbon emissions for both products; otherwise, the unit outsourcing cost under the carbon-trade policy is higher. (3) Both policies lessen the total environmental implication. When the upper limit of carbon emissions is less than a particular threshold, the environmental effect of the two manufacturers under the carbon-emission-constraint policy is smaller; otherwise, the environmental impact is smaller under the carbon-trade policy.

Hyperspecialization and hyperscaling: A resource‐based theory of the digital firm

AbstractResearch SummaryDigital firms tend to be both narrow in their vertical scope and large in their scale. We explain this phenomenon through a theory about how attributes of firms' resource bundles impact their scale and specialization. We posit that highly scalable resource bundles entail significant opportunity costs of integration (vs. outsourcing), which simultaneously drive “hyperspecialization” and “hyperscaling” in digital firms. Using descriptive theory and a formal model, we develop several propositions that align with observed features of digital businesses. We offer a parsimonious modeling framework for resource‐based theorizing about highly scalable digital firms, shed light on the phenomenon of digital scaling, and provide insights into the far‐reaching ways that technology‐enabled resources are reshaping firms in the digital economy.Managerial SummaryWhy are leading firms in the digital economy simultaneously larger and more specialized than those in the industrial age? Our research explains this phenomenon as being driven by the scalability of digital resources—that is, their capacity to create more value at larger scales when used intensively in a focal activity. We clarify what digital scalability means, and highlight trade‐offs created by the opportunity costs of not employing scalable digital resources intensively. Digital firms should outsource complementary activities to avoid diverting resources away from their scalable core, and to enhance their ability to grow exponentially. Although resource fungibility and outsourcing costs mitigate these imperatives, digital firms may nonetheless find it profitable to remain specialized despite the challenges of managing outsourcing and sharing value with complementors.

Coordinated scheduling of the outsourcing, in-house production and distribution operations

In this paper we study coordinated scheduling of the outsourcing, in-house production and distribution operations. In our integrated scheduling model, each job is either outsourced by paying a cost, or processed by one of the in-house machines. Processed jobs are delivered in batches by vehicles with identical capacities, where each job has a non-identical physical size. The objective is to determine the subsets of jobs to be outsourced and a joint production and delivery schedule for the rest of the jobs that are processed in-house, so that the makespan of the jobs processed in-house plus the total cost of outsourcing and delivery is minimized. The proposed scheduling problem is strongly NP-hard. We formulate the scheduling problem into a neat mixed integer programming (MIP) and present an efficient 2-approximation algorithm. We also develop a sophisticated (32+ϵ)-approximation algorithm, where ϵ∈(0,1) can be any small constant. The performance of the proposed algorithms is evaluated through numerical experiments.

A Two-Level Optimization Approach For Engineer-To-Order Project Scheduling*

This paper presents a new formulation of the flexible job-shop scheduling problem with outsourcing options adapted for Engineer-To-Order (ETO) products. Our formulation enables modeling complex product structures with flexible precedence relations between elements and operations. Having a significant role in the ETO context, the specificity of non-physical operations (design and engineering) is taken into account. Indeed, non-physical operations are subject to a validation stage, can be iterated in case of non-validation, and are executed once for several identical elements. The proposed approach is governed by a new ETO strategy to overcome the impact of the design uncertainty and element cancellations (time and financial wastes). First, the production and purchase of the most uncertain elements are delayed at the latest while their design is validated early. Besides, in the presence of similar elements, an element can be saved when cancelled by being used as a sub-part of another one. The proposed approach sequentially solves two mathematical models. The first model aims to minimise the makespan and outsourcing costs. The second model maximizes the solution robustness and the ability of saving elements while being governed by the completion time and project cost, output of the first model. The obtained results and a comparative study show the efficiency and robustness of the proposal.

Outsourcing in supply chain: A bibliometric analysis

The purpose of this paper is to conduct a bibliometric analysis to analyze trends and patterns of outsourcing and supply chain research results using statistical and co-word analysis. The search results in the Scopus database yielded 787 relevant documents with the keywords outsourcing and supply chain from 1997 to early 2022. The results of the bibliometric analysis resulted in the number of publications, citations, subject areas, country, keywords, and topic clusters. The trend of outsourcing and supply chain research tends to increase every year although it had a significant decline in 2011. The documents with the most citations are related to supplier selection using analytical network processes, optimization of outsourcing partners, and ICT in the supply chain. The four fields that dominate the research area are business management, engineering, decision science, and computer science. The United States of America is the most productive country with the most citations. There are four cluster topics formed: the importance of supply chain management in outsourcing in industry and ICT in company activities, the impact of supply chain on business performance and outsourcing decisions, logistics outsourcing decisions to third parties and their effectiveness, lastly the benefit costs of outsourcing and the implications for product management. This paper provides an additional updated overview of the outsourcing and supply chain research map.

Single Machine Scheduling Problem with Batch Outsourcing

Outsourcing as a useful strategy in the industry can be integrated into scheduling problems. Moreover, batch outsourcing is a practical assumption owing to the logistics issues for transferring the parts between the manufacturer and the subcontractors. However, this assumption is rarely addressed in the scheduling literature. In this paper, a novel single machine scheduling problem with the option of batch outsourcing is studied. The objective is to minimize the sum of the total completion time of the jobs and the total outsourcing cost. To solve the problem, first, two mixed-integer linear programming (MILP) models, named MP1 and MP2, are developed, which respectively use a straightforward and an innovative approach to model the outsourcing batches. Next, an optimal property for the outsourcing batches is proven. This property is used to establish a valid inequality for model MP2, which is added to it to obtain a third MILP model, MP3. Extensive computational experiments showed that MP2 outperforms MP1 significantly. Moreover, including the derived valid inequality in MP3 enhances its performance considerably in comparing to MP2. Furthermore, it is observed that MP3 is capable of solving many practical-size problem instances optimally or with a low maximum optimality gap.

The Impact of Carbon Trade on Outsourcing Remanufacturing.

Outsourcing remanufacturing is an important way to achieve resource recycling, green manufacturing and carbon neutrality goals. To analyze the impact of carbon trade on manufacturing/remanufacturing under outsourcing remanufacturing, this article builds a game model between an original equipment manufacturer (OEM) and a remanufacturer under the carbon trade policy. In the outsourcing remanufacturing model, this article compares the impact of the carbon trade policy on the unit retail price, sales volume, revenue, environmental impact, and consumer surplus of new and remanufactured products. The research mainly draws the following conclusions: (1) Carbon trade increases the prices of both new and remanufactured products and the cost of outsourcing. Only when certain conditions are met can increased carbon trade prices increase revenue. (2) The carbon trade policy helps reduce the adverse impact on the environment, but only when the carbon trade price is greater than a certain threshold can it increase consumer surplus. (3) Consumer preferences and carbon emissions of the unit product affect manufacturers’ profits. Increased consumer preference for remanufactured products and reduced carbon emissions of remanufactured products contribute to increased sales and revenues.

Organic waste derived biodiesel supply chain network: Deterministic multi-period planning model

In this study, a multi-period model of an organic waste-to-biodiesel phased supply chain network is developed to strategically consider variations in the biodiesel demand and the organic waste usage over a long-term planning interval. The proposed model can facilitate planning to determine the biorefinery location and the amount of biodiesel to produce, transport, or utilize to reduce the total cost of the organic waste-to-biodiesel supply chain network design while meeting the biodiesel demand during each period of the planning interval. The features and capabilities of the model are validated by application of a future organic waste-to-biodiesel supply chain network design in South Korea. The optimization results illustrate that the average total annual cost of the organic waste of biodiesel based on the multi-period model will be $US 4.2 billion per year during the period 2020–2030. The minimum selling prices for the optimal network design were determined ranged from $US 3.154–3.156/gallon of biodiesel containing 3% butanol derived from organic waste combined with diesel. A small portion (4.9–6.6%) of the total biodiesel demand was produced from organic waste because of low organic waste availability in the existing anaerobic digestion facilities, leading to increasing the outsourcing costs of butanol. The proposed approach will facilitate the strategic development of a sustainable supply chain network for organic waste recycling for material and energy valorization.

Scheduling on flexible flow shop with cost-related objective function considering outsourcing options

This study considers outsourcing decisions in a flexible flow shop scheduling problem, in which each job can be processed by either an in-house production line or outsourced. The selected objective function aims to minimize the weighted sum of tardiness costs, in-house production costs, and outsourcing costs with respect to the jobs due date. The purpose of the problem is to select the jobs that must be processed in-house, schedule processing of the jobs in-house, and finally select and assign other jobs to the subcontractors. We develop a mixed-integer linear programming (MILP) model for the research problem. Regarding the complexity of the research problem, the MILP model cannot be used for large-scale problems. Therefore, four metaheuristic algorithms, including SA, GA, PSO, hybrid PSO-SA, are proposed to solve the problem. Furthermore, some random test problems with different sizes are generated to evaluate the effectiveness of the proposed MILP model and solution approaches. The obtained results demonstrate that the GA can obtain better solutions in comparison to the other algorithms.

An improved algorithm for a two-stage production scheduling problem with an outsourcing option

We consider a two-stage production scheduling problem where each operation can be outsourced or processed in-house. For each operation in the same machine, the ratio of its outsourcing cost to its processing time is constant. The objective is to minimize the sum of the makespan and the total outsourcing cost. It is known that this problem is either polynomial time solvable or NP-hard according to the conditions of the ratios. Even though approximation algorithms for NP-hard cases had been developed, their tight worst-case performance ratios are still open. In this paper, we carefully analyze the approximation algorithms to identify their tight worst-case performance ratios for cases. In one case, we propose a new approximation algorithm with a better and tight worst-case performance ratio. In the process of analyzing the algorithm, we propose a technique utilizing nonlinear optimization.

K-adaptability in robust container vessel sequencing problem with week-dependent demands of a service route

ABSTRACT This work investigates a robust container vessel sequencing (RCVS) problem in a service route. As weekly demands vary dramatically and cannot be forecasted accurately, shipping companies need to develop a robust sequence of vessels with different capacities to maximally meet demands. As export heavily depends on economy, demands may share the same pattern in adjacent years, which motivates us to study the problem in a cyclic fashion. To refine the literature, we adopt a robust optimisation model to minimise the worst-case total cost, including container tardy and outsourcing cost, due to reliability guarantee. To accommodate human decision-making, we focus on an associated K-adaptability problem, which pre-selects a number of candidate vessel sequences and implements the best one when the uncertain demands have been observed. A branch-and-bound solution approach is explored. Numerical experiments demonstrate the performance of our approach.

How to Boost the Payoff from Innovation While Shrinking its Destructive Side Effects

Gather a group of economists together and ask what most concerns them, and a wide variety of topics would soon emerge: slowing economic growth in the rich nations, the inability of many poor nations to converge toward the rich, rising income and wealth inequality, the increasing dominance of superstar firms, growing profit margins and the decline in labor's income share, globalization and the human costs of outsourcing, deaths of despair, and the threat of climate change. Decade after decade, numerous books have been written about each of these issues. But here we have in one compact package a blockbuster book that deals with all of them.

Research on optimization of distribution route for cold chain logistics cooperative distribution of fresh e-commerce based on price discount

In order to solve the problem that the development of self-built logistics cannot meet the development of fresh e-commerce, a coordinated distribution strategy of self-built logistics and third-party logistics is proposed. The tasks assigned by third-party logistics are used to determine the price discount ratio. Third-party distribution outsourcing cost function, customer satisfaction function, and freshness function of fresh produce. Aiming at the goal of minimum delivery cost, maximum customer satisfaction, and maximum freshness of fresh produce, a collaborative delivery optimization model was established, and a corresponding genetic algorithm was designed with examples. Simulation results show that: collaborative distribution can effectively reduce the cost of distribution, when the proportion of price discount increases, the cost of collaborative distribution decreases. It has a certain reference value for the optimization of fresh e-commerce enterprises’ distribution mode.

The hub location problem with market selection

We propose a hub location problem with market selection. The problem has a given number of markets with each market associated with predetermined demand and fixed revenue. The selected market demand has to be shipped from the origin to the destination via a hub-and-spoke system. The overall objective is to maximize the overall margins that are equal to the total revenue of the selected markets minus the total costs, including the leasing costs of hubs, transportation costs, and outsourcing costs. We propose a mixed integer programming model to formulate the problem with service and flow capacity constraints. For this problem, we propose a subgradient-based Lagrangian relaxation method that exploits the rich structure of the Lagrangian subproblems to obtain its objective values and bounds efficiently. Specifically, we treat the Lagrangian subproblems as knapsack problems and solve them by using a dynamic programming method. Furthermore, we propose a polynomial algorithm to quickly generate objective values of the original problem at each iteration of the Lagrangian relaxation. Computational results show that the proposed method can obtain optimal solutions for small-sized test instances and achieve much better solution qualities than the commercial software package (Cplex) for large-sized test instances. The proposed method also achieves better solutions than a Benders decomposition method for the tested instances.

Perceived supplier opportunism in outsourcing relationships in emerging economies

AbstractWhile opportunism has been a focus of transaction cost economics, perceived opportunism, where one party is perceived to be acting opportunistically when there is no opportunistic intent, can also lead to increased transaction costs in an exchange. In this study, consistent with forms of opportunism observed in our context of manufacturing outsourcing, we examine two different forms of perceived opportunism—perceived poaching and shirking. As narratives of the hidden costs of outsourcing discuss concerns of suppliers in emerging economies engaging in poaching and shirking, we examine if the level of economic development where a supplier operates affects perceptions of supplier poaching and shirking and also examine if the supplier's competitive priorities moderate those perceptions. To empirically test these relationships, we combine archival data of location characteristics with a dyadic primary dataset that captures perceived supplier opportunism, self‐reported supplier opportunism, and other relationship characteristics. Our findings illustrate that perceived opportunism and opportunism are distinct constructs and that more observable forms of opportunism (i.e., shirking) affect perceived opportunism more than less observable forms of opportunism (i.e., poaching). We also find that, in existing relationships, manufacturers in advanced economies perceive poaching to be more strongly related to the level of economic development where a supplier operates than shirking. Finally, we find that while a cost focus can mitigate perceptions of poaching, an innovation focus exacerbates them. Overall, our study illustrates the challenges that innovation‐focused suppliers in emerging economies face in regards to competing with suppliers in advanced economies.

Does Global Outsourcing Affect Corporate Customers’ Voluntary Disclosures?

Reliance on global supply chains (GSCs) has become an economic imperative for many major corporations worldwide, but at the same time, it has brought substantial risks and complexities to these firms. This study examines whether global outsourcing of goods or services shapes U.S. corporate disclosure policies. Our main results suggest a negative impact of GSC exposure on voluntary disclosure, and several identification tests further support this baseline evidence. We find that the adverse effect on disclosure is more pronounced when institutional differences are more significant between the U.S. and foreign suppliers’ countries and when U.S. firms face higher litigation risks. However, the effect weakens when investors and stakeholders demand more information. Collectively, from an information disclosure perspective, our study provides new insights into the potential costs of outsourcing globally, leading to a reduction in forward-looking information provided to capital markets.

Multi-product production routing problem by consideration of outsourcing and carbon emissions: particle swarm optimization

Studies have shown that the production and routing problems have an impact on each other, and the integration of these decisions can considerably improve decision making and reduce costs. In this regard, this research studies the effect of outsourcing on a multi-product production routing problem considering environmental impact. In addition to minimizing greenhouse gas emission costs, in this study, the objective function of the problem includes production, maintenance and outsourcing costs. After modelling the problem as mixed-integer linear programming, because of its NP hardness, a particle swarm optimization (PSO) algorithm is also proposed for solving the problem, especially in large-size instances. To verify the effectiveness of the proposed algorithm, a set of random test problems with different structures is generated. Finally, the PSO and variable neighbourhood search (VNS) algorithms are compared, and the results show that the PSO is better than the VNS algorithm.

The Vehicle Routing Problem with Partial Outsourcing

This paper introduces the vehicle routing problem with partial outsourcing (VRPPO) in which a customer can be served by a single private vehicle, by a common carrier, or by both a single private vehicle and a common carrier. As such, it is a variant of the vehicle routing problem with private fleet and common carrier (VRPPC). The objective of the VRPPO is to minimize fixed and variable costs of the private fleet plus the outsourcing cost. We propose two different path-based formulations for the VRPPO and solve these with a branch-and-price-and-cut solution method. For each path-based formulation, two different pricing procedures are designed and used when solving the linear relaxations by column generation. To assess the quality of the solution methods and gain insight in potential cost improvements compared with the VRPPC, we perform tests on two instance sets with up to 100 customers from the literature.

Shift Planning Under Delay Uncertainty at Air France: A Vehicle-Scheduling Problem with Outsourcing

Airlines must operate many jobs in airports, such as passenger check-in or runway tasks. In airlines’ hubs, airlines generally choose to perform these jobs with their own agents. Shift planning aims at building the sequences of jobs operated by the airline agents and has been widely studied given its impact on operating costs. The impact of delayed flights is generally not taken into account despite the propagation of flight delays along these sequences: If a flight is late, then the agents doing the corresponding jobs are delayed, and may arrive late to their next jobs and delay the corresponding flights. Since delay costs are much higher than the costs of outsourcing jobs, if the agent who is supposed to operate a job is still working elsewhere when the job begins, then airlines tend to outsource the job to their own dedicated team or to a third party. We introduce a stochastic version of the shift-planning problem that takes into account outsourcing costs due to delay. It can be seen as a natural stochastic generalization of the vehicle-scheduling problem in which delayed jobs are outsourced. We propose a column-generation approach to solve it, whose key element is the pricing subproblem algorithm, modeled as a stochastic resource-constrained shortest-path problem. Numerical results on Air France industrial instances show the benefits of using our stochastic version of the shift-planning problem and the efficiency of the solution method. Moving to the stochastic version enables Air France to reduce total operating costs by 3.5%–4.8% on instances with more than 200 jobs, and our algorithm can solve to near optimality instances with up to 400 jobs.