By building a game model between brands and outsourced anchors, this article systematically studies the incentive design, opportunistic behavior and blockchain governance mechanism in live streaming. We found that while promoting the sales efforts of anchors, commission incentives will also induce opportunistic behaviors such as AI rhetoric exaggeration, traffic manipulation and channel encroachment. Secondly, blockchain technology can effectively suppress opportunism by improving the traceability of information and the verifiability of behavior: on the one hand, it increases the marginal cost of implicit violations, On the other hand, contractible punishment is imposed on explicit sexual encroachment. The key threshold conditions in the study show that when the sum of the incentive intensity and the blockchain punishment exceeds the encroachment of personal interests, the encroachment can be completely suppressed. The study further reveals the three-state equilibrium model of the optimal blockchain governance intensity: strong governance, weak governance and precise governance. Its choice depends on the trade-off of product characteristics, incentive costs and governance benefits. At the same time, the governance effect is affected by the power structure of the platform, and the platform, as a provider of governance infrastructure, may have the problem of insufficient motivation. Based on this, this article proposes that the sustainable development of live ecology requires building a comprehensive system of incentive contracts, technical governance and institutional environment coordination. It also provides a theoretical framework for understanding the problem of entrusted agencies in digital marketing and a decision-making basis for the governance practice of the platform economy.

This study examines the joint impact of outsourcing, overtime, multi-delivery, rework, and postponement on a multiproduct fabrication problem. A growing/clear trend in today’s customer requirements turned into rapid response and desired quality of multi-merchandises and multiple fixed-amount deliveries in equal-interval time. To satisfy customers’ expectations, current manufacturing firms must effectively design/plan their multiproduct production scheme with minimum fabrication-inventory-shipping expenses and under confined capacity. Motivated by assisting manufacturing firms in making the right production decision, this study develops a decision-support delayed-differentiation model considering multi-shipment, rework, and dual uptime-reducing strategies (namely, overtime and outsourcing). Our delayed-differentiation model comprises stage one, which makes all common/standard parts of multi-end-merchandises, and stage two, which produces multiple end merchandise. For cutting making times, the study proposes subcontracting a portion of the common/standard part’s lot size and adopting overtime-making end merchandise in stage two. The screening and reworking tasks identify and repair faulty items to ensure customers’ desired quality. The finished lots of end merchandise are divided into a few equal-amount shipments and distributed to customers in equal-interval time. We employ mathematical derivation and optimization methodology to derive the annual expected fabrication- inventory-shipping expense and the cost-minimized production-shipping policy. A numerical demonstration is presented to exhibit our research scheme’s applicability and exposes the studied problem’s critical managerial insights, which help the management make beneficial decisions.

Production management operating in recent competitive marketplaces must satisfy the client desired quality and shorter order lead-time and avoid internal fabricating disruption caused by inevitable defects and stochastic equipment failures. Achieving these operational tasks without undesirable quality goods, missing due dates, and fabrication interruption help the management minimize operating expenditures. Motivated by assisting manufacturing firms in the situations mentioned this study explores a manufacturing system that features quality reassurances through reworking or removal of defectives, correction of probabilistic failures, and partial overtime and outsourcing options for reducing uptime. This study finds the function of system operating expenditures through model building, mathematical formulations, optimization approaches, and algorithm proposition, shows its convexity, and derives the optimal batch time for the studied manufacturing model. Finally, this study offers numerical illustrations to confirm our work’s applicability and disclose its capability to provide various profound crucial system information that helps the management make strategic operating decisions.

Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem.

A hybrid batch fabrication plan involving an outsourcing option is often established to deal with the in-house capacity constraint and/or meet timely demand with a reduced cycle time. Besides, the occurrences of unpredictable equipment malfunction and imperfect product quality should also be effectively managed during in-house fabrication to meet the production schedule and the required quality level. To address these concerns, we examine a hybrid economic production quantity (EPQ) problem with an unreliable machine and quality reassurance; wherein, an outside provider helps supply a portion of the batch at a requested timing and desirable quality, but at the price of a higher than in-house unit cost. Corrective action is performed immediately when a Poisson-distributed breakdown occurs. Once the equipment repairing task completes, the interrupted lot’s fabrication resumes. Random nonconforming products are identified, and the re-workable items among them are separated from the scraps. A rework task follows the regular process in each cycle at an extra cost. A portion of reworked items fails and are scrapped. A model portraying the problem’s characteristics is built, and an optimization methodology is utilized to find the optimal runtime solution to the problem. A numerical example reveals our result’s applicability, and specific managerial implications are suggested.

Production planners today must simultaneously face with the time and quality demands of various goods externally and meet limited capacity internally. This study presents a two-stage delayed- differentiation multiproduct model that considers the outsourcing options for common parts, overtime strategy for end products, and quality reassurance to assist in making fabrication runtime decisions that are cost-effective. Stage one produces all necessary common intermediate components for end products. To reduce stage one’s utilization/uptime, this study adopts a partial outsourcing option. Stage two uses an overtime strategy to fabricate end products that further shorten the uptime. The production processes in both phases are assumed to be imperfect. This study employs the reworking/scrapping of random faulty items to reassure product quality. The researchers build a model to depict the proposed problem’s characteristics and used the mathematical modeling, analysis, and optimization approach to determine the best rotation cycle length that minimizes the system’s expenses. Further, in this study, the researchers provide sensitivity analyses and a numerical illustration, which validate the result’s applicability and exhibit its capability. This result contributes to practical multiproduct-fabrication by (1) deriving the optimal manufacturing policy for a delayed-differentiation multiproduct system with dual uptime reduction policies and quality reassurance; and (2) offering a decisional model that allows production planners to explore the collective/separate effect of a quality-ensured and dual uptime reduction strategy on a problem’s operating policy and crucial system performance indicators, which assists in cost-effective decision-making.

Variety, quality, and rapid response are becoming a trend in customer requirements in the contemporary competitive markets. Thus, an increasing number of manufacturers are frequently seeking alternatives such as redesigning their fabrication scheme and outsourcing strategy to meet the client’s expectations effectively with minimum operating costs and limited in-house capacity. Inspired by the potential benefits of delay differentiation, outsourcing, and quality assurance policies in the multi-item production planning, this study explores a single-machine two-stage multi-item batch fabrication problem considering the abovementioned features. Stage one is the fabrication of all the required common parts, and stage two is manufacturing the end products. A predetermined portion of common parts is supplied by an external contractor to reduce the uptime of stage one. Both stages have imperfect in-house production processes. The defective items produced are identified, and they are either reworked or removed to ensure the quality of the finished batch. We develop a model to depict the problem explicitly. Modeling, formulation, derivation, and optimization methods assist us in deriving a cost-minimized cycle time solution. Moreover, the proposed model can analyze and expose the diverse features of the problem to help managerial decision-making. An example of this is the individual/ collective influence of postponement, outsourcing, and quality reassurance policies on the optimal cycle time solution, utilization, uptime of each stage, total system cost, and individual cost contributors.

Operating in today’s highly competitive global markets, transnational enterprises always seek to optimize internal vendor-buyer coordinated systems to ensure timeliness and quality deliveries, given the reality of unreliable machines and limited capacity. To facilitate accurate decision making to help organizations gain competitive advantages in such situations, this study explores an intra-supply-chain problem featuring a partial outsourcing batch fabrication plan, random scrap, Poisson-distributed breakdown rate, and multiple shipments of end-product. First, we build a model to characterize the problem clearly. Then, we carry out formulations, analyses, and derivations of the model to attain the problem’s cost function. We then use differential calculus and propose a specific algorithm to confirm the convexity of the obtained cost function and derive the optimal runtime. Finally, we offer a numerical illustration to demonstrate the result’s applicability for other business circumstances. Additional elements of the problem are then discussed, including the individual and combined influence of variations in scrap, outsourcing, breakdown, and shipping frequency. The features of an optimal operating policy and cost relevant parameters are now revealed to assist management with strategic planning and decision making in real-world intra-supply-chain environments.

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.

This study aims to propose and apply a systematic and descriptive presentation of the costs of administrative coordination and organizational costs for a third-party company in the manufacturing enterprises of individual business functions. As for the procedures, it is a bibliographic research, based on Design Science Research, which proposes a new artifact based on the review of the literature and which starts to be applied based on the Iraqi Financial Control Council and Financial rules followed to achieve financial discipline. Special methods in which it was chosen to apply techniques such as observation, it is a practical means of cognition determining costs revenue that help to understand and identify the problems of the implementation of the main functions of financial, accounting and administrative performance. The research proposes the classify costs according to the types of industrial objects, contracts, and agreements based on the requirements of standard No. 1 “Measurement of performance results under employment contracts.