Service Supply Chain Research Articles

Application of intelligent logistics inventory optimization algorithm based on digital supply chain

Abstract Inventory is the core link of enterprise operation and an essential resource for enterprises to occupy the market. Therefore, optimizing the control and management of inventory is a necessary measure for enterprises to maintain their core competitiveness. However, at present, the optimization of the enterprise’s inventory is basically still at the single inventory level, which seriously shortens the life cycle of the enterprise’s products and reduces the speed of the enterprise’s capital flow. Digital supply chain is the digitization of traditional supply chain services, which can change the traditional thinking of inventory control and management, break down the barriers between enterprises and modern logistics, and build a complete management system for enterprises. Smart logistics is a product of the new era, and it is also a product of the development of the digital supply chain. To this end, this paper proposes an inventory optimization algorithm based on digital supply chain and smart logistics. The algorithm is optimized on the basis of the original inventory optimization scheme, so that the improved algorithm can be more suitable for actual inventory management needs. The experimental results of this paper show that the improved new inventory optimization algorithm improves the comprehensive benefit by 39.1% on the original basis, which can effectively reduce the error in the actual use process.

Enhancing Operational Performance of Indonesia Pine Chemical Industry Through Delivery Improvement

Pine chemical products, namely gum rosin and turpentine oil have become one of the main exported non-timber forest products (NTFPs) from Indonesia. As the biggest pine chemical producer in Indonesia, a State Owned Enterprise named Perum Perhutani is required to operate at its optimum capability. Hence, this study aims to identify and measure some dimensions of operational capability that have the most influence on increasing the export performance of Perhutani. The data are collected through online survey from 207 Perhutani employees who work in pine chemical production lines. Four-point Likert Scale questionnaires are employed to collect the data regarding respondent’s perception on seven dimensions of operational capability, namely Cost, Quality, Delivery, Flexibility, Service, Innovation, and Sustainability. R statistics software is selected to run the tests. By adopting Tukey HSD, a multiple pairwise-comparison technique, Delivery is rated as the most important dimension to enhance export performance. It is significantly proven to have the highest mean score. Another finding indicates that Delivery is found to have fair to moderate correlation to other dimension which directly involved in supply chain activities, i.e. Cost, Quality, Flexibility, and Service. Therefore, this study demonstrates a need for Perhutani top management to set minimum and expected targets of some key indicators of Delivery performance such as on-time delivery, delivery accuracy, length of lead-time, and safe inventory level. The higher the rate of on-time and in-full (OTIF) delivery fulfilled, the higher the opportunity to achieve a better export performance of pine chemical products.

Service supply chain resilience: a social-ecological perspective on last-mile delivery operations

PurposeConsidering the last-mile delivery service supply chain as a social-ecological system rather than just a firm-based service system, this research exploit the COVID-19 pandemic disruption to investigate how the supply chain develops resilience from a viewpoint that integrates a social-ecological perspective with the traditional engineering one.Design/methodology/approachThis research adopt a multi-case study approach using qualitative data collected via semi-structured interviews with executive-level managers from nine leading UK last-mile delivery companies. Data analysis is guided by a research framework which is developed by combining the social-ecological perspective with the structure–conduct–performance paradigm. This framework aids the investigation of the impacts of external challenges on companies' resilience strategies and practices, as well as performance, in response to disruptions.FindingsThe research identifies three distinct pathways to resilience development: stabilization, focussing on bouncing back to the original normal; adaptation, involving evolutionary changes to a new normal; transformation, involving revolutionary changes in pursuit of a new normal-plus. Three strategic orientations are identified as operating across these pathways: people orientation, digital orientation, and learning orientation.Originality/valueIn contrast to the manufacturing supply chain focus of most current research, this research concentrates on the service supply chain, investigating its resilience with a social-ecological perspective alongside the traditional engineering one.

Research on the Emission Reduction Decision of Cost-Sharing Logistics Service Supply Chain in the O2O Model

As an effective way to realize energy savings and environmental protection, cost sharing is gradually becoming an important measure to reduce emissions in the logistics service supply chain under O2O mode in recent years. How to conduct contract selection and design optimization under the cost-sharing situation, and then improve the operational efficiency of the logistics service supply chain is an important issue that needs to be addressed. Firstly, based on the initial market demand for logistics, this paper involves the influence of both online logistics service integrators and onsite functional logistics service providers on logistics market demand in terms of emission reduction and platform brand image and develops a model based on the logistics service demand function in the O2O mode. Secondly, for the role of online and onsite emission reduction services in multi-cycle continuous cooperation to enhance the platform integrator’s brand image, a cost-sharing differential game model between online and onsite services is developed to facilitate providers’ adoption of high-quality emission reduction services. Finally, the HJB equation is used to compare the non-cooperative Nash game, the cost-sharing Stackelberg game, and the cooperative game to make the optimal abatement decision, the optimal benefit, and the cost-sharing ratio of the abatement service supply chain in the non-cooperative Nash game, the cost-sharing Stackelberg game, and the cooperative game. By comparing the results of the three games, we find that the optimal onsite and online abatement service decision is related to the cost, marginal revenue, and the impact of the service on demand; the abatement cost-sharing contract and cooperation are both better than the non-cooperative independent decision state, which can effectively guide the provision of high-quality onsite abatement service and improve the revenue of both parties involved in the logistics service supply chain and the total system’s revenue in the O2O mode. Compared with the cooperative game model, the cost-sharing contract can more effectively facilitate close cooperation between the actors, and the relationship between onsite and online marginal revenue affects the improvement of both parties’ revenue. The findings of the study can provide useful managerial insights for the selection and design optimization of abatement contracts for logistics service supply chains considering cost-sharing via the O2O model.

A supply chain management framework for services

AbstractWhile services represent the largest sector of the global economy, 86.8% in the United States, most supply chain management (SCM) research is focused on product flows. Executives in manufacturing firms have benefited from frameworks created to implement SCM processes, but this is not the case for their counterparts in service companies. The two most cited SCM frameworks for services have methodological and conceptual deficiencies. Drawing upon the service‐dominant logic of marketing and using an empirical research approach, we developed supply chain structure maps for nine service firms. Our findings indicate that the supply chain structure maps of service companies are comparable to those in the product‐based literature, which supports the service‐dominant logic. Then, we identified the six key processes that constitute a framework to manage service supply chains. The customer relationship management and the supplier relationship management processes form the critical links in the supply chain, and the other four processes are coordinated through this linkage. The SCM framework for services provides direction for executives in service firms who need to increase cross‐functional integration within their firms and with other members of the supply chain. For academics, 12 avenues for future research are identified.

Logistics Service Supply Chain Decision-Making Analysis Considering Impact of Environment and Service Level

Logistics Service Supply Chain Decision-Making Analysis Considering Impact of Environment and Service Level

Price Decision-Making in Dual-Channel Healthcare Services Supply Chain Considering the Channel Acceptance, Price Ceiling, and Public Welfare.

Given that an increasing number of online healthcare channels play an essential role as a supply method in the healthcare service supply chain (HSSC), this paper studies the price decision-making problem for a dual-channel HSSC considering the channel acceptance, price ceiling, and public welfare. In this HSSC, a healthcare institution establishes both a traditional offline channel and an online channel to provide healthcare services for some health conditions. Considering the public welfare of healthcare institutions, we employ a sum formula of economic revenue and patient surplus to describe the total revenue of both healthcare service channels. Based on the Stackelberg game, we develop a decentralized supply chain model to maximize supply chain members’ revenue. By employing the –– optimality condition, we derive an analytical expression for the optimal service price, which includes the functions of the public welfare coefficient and channel acceptance. Finally, we conduct extensive numerical analyses under various system parameters to verify the optimal price decision-making strategies. Our analytical results indicate that: (1) the healthcare service price is closely related to the patients’ channel acceptance, the public welfare coefficient, and the government price ceiling policy; (2) the public welfare coefficient strongly influences the service price and total revenue, and its increase can decrease the economic revenue of the HSSC; (3) the acceptance of online channels is an essential factor that should be carefully considered in the construction of a dual-channel HSSC. Improving patient acceptance of online channels is conducive to developing and improving a sustainable dual-channel HSSC.

A Stochastic Programming Model for Jointly Optimizing Maintenance and Spare Parts Inventory for IoT Applications

Service supply chain models typically use conservative maintenance and spare part management policies that result in significant losses due to redundancies. Conservatism without an improved understanding of risks, however, does not cushion against unexpected consequences. Risk scenarios associated with asset failure and inventory shortage are frequently observed in practice. Advances in Internet of Things (IoT) technology is unlocking new methods that attain significant prediction accuracy for these risk factors. IoT-enabled predictions on asset state of health can drive dynamic decision models that conduct maintenance and replenishment actions more efficiently while reducing risk. In this study, we propose a unified framework that utilizes IoT data to jointly optimize condition-based maintenance and inventory decisions. We formulate our problem as a stochastic mixed integer program that accounts for the interplay between maintenance, spare parts inventory, and asset reliability. We introduce a new reformulation that’s efficient for solving large-scale instances of the proposed model. The framework presented herein is applied to real world degradation data to demonstrate the benefits of our methodology in terms of cost and reliability.

Effects of channel power structures on pricing and service provision decisions in a supply chain: A perspective of demand disruptions

This paper investigates the service investment and pricing decisions under different power structures when there exist demand disruptions. We consider a supply chain consisting of a single manufacturer and a single retailer, and establish a game theory model under three typical channel power structures: Manufacturer Stackelberg game, Retailer Stackelberg game, and Nash game. We find that when the demand is disrupted, whether it is a centralized system or decentralized system with different power structures, the service level and production quantity are robust when the demand disruption is sufficiently small, and the wholesale price is also robust under certain circumstance. The comparison results of equilibrium pricing and service level under different power structures are affected by the supply chain power and service cost coefficient no matter who provides the demand-enhancing services. Moreover, it can be found that the power structure most suitable for the manufacturer or the retailer is not invariable and the results are related to the change of some parameters.

Analytics applications, limitations, and opportunities in restaurant supply chains

Technology, market, and competitive dynamics are requiring firms in restaurant/food service supply chains to improve their analytics capabilities, which have tended to lag behind other comparable industries. The global COVID‐19 pandemic has further encouraged industrial leaders to evaluate new challenges and opportunities. Our research provides insights into current applications of analytics technologies and organizationally integrates these insights for decision‐makers in restaurant supply chains. The study applies decision theory as a framing perspective to this phenomenon, thereby advancing the academic literature on the interface between data management, analytical techniques, and computing. We combine data drawn from interviews of leading players in U.S. and Chinese‐based restaurant chains with insights from trade publications and social media posts to identify best practices for analytics usage and supporting organizational changes. Our analysis provides examples of ways in which business leaders are applying analytics technologies to structured and unstructured data to address targeted objectives for demand/supply processes and to foster higher order organizational learning. In keeping with the stated objectives of this special issue of Production and Operations Management, this study provides an overview of both current state‐of‐the‐art and next‐generation capabilities for analytics in the restaurant industry. We further identify specific limitations of current processes, opportunities for development and theory‐based research, and challenges to implementation.

Pricing of platform service supply chain with dual credit: Can you have the cake and eat it?

Pricing of platform service supply chain with dual credit: Can you have the cake and eat it?

Taxonomy of Small and Medium Enterprises (SMEs) Constraints: An Analytical Perspective of Zimbabwe

Small and medium-sized enterprises (SMEs) in Zimbabwe are regarded as the most resilient and the backbone of the economy following years of capital flight since 2000 following the consummation of the fast tract land reform programme. Since then, major corporates disinvested, and this created a huge gap in the products and services supply chain, and the SMEs robustly emerged largely owned by the local people. This paper, however, has established that in as much as the SMEs have a critical role to play, government aided financing infrastructure is characterised by a plethora of policy and regulatory frameworks that limit growth and development of the SMEs to contribute significantly to the development of the economy. Using a review process as a methodology as part of an ongoing doctoral research in this field, the paper puts across that it is vitally important for Zimbabwe to put incentives from a policy and tax rebate point of view, including lessening the bureaucratic red-tape and rigidities that characterise SMEs loan application to access to capital. The various independent and dependent variables in this paper require an overhaul to ensure that the challenges that limit SMEs access to financing are addressed.

Logistic Analytics Management in the Service Supply Chain Market Using Swarm Intelligence Modelling

The industry sustainability in today's globalization relies on cost-effective supply chain management of diverse markets and logistics. Supply chain risks typically limit profits over the overall expense of the supply chain. In the supply chain design practices, the volatility of demand and limitations of levels are essential concerns. In this paper, a swarm intelligence-assisted supply chain management framework (SISCMF) has been proposed to increase profit and improve logistics performance. Due to the simplicity of design and rapid convergence, swarm intelligence (SI) algorithms are widely used in most supply network design fields and efficiently solve large-dimensional problems. A significant increase in resolving these problems has been seen in particle swarm optimization and ant colony algorithm. The simulation result suggested the operational cost (92.7%), demand prediction ratio (95.2%), order delivery ratio (96.9%), customer feedback ratio (98.2%), and product quality ratio (97.2%).

The Security Value of Small and Medium Sized Ports in a Supply Chain Service

The Security Value of Small and Medium Sized Ports in a Supply Chain Service

Assessing catchment scale water quality of agri-food systems and the scope for reducing unintended consequences using spatial life cycle assessment (LCA).

Life cycle assessment is a multidisciplinary framework usually deployed to appraise the sustainability of various product or service supply-chains. Over recent decades, its use in the agri-food sector has risen sharply, and alongside this, a wide range of methodological advances have been generated. Spatial-life cycle assessment, defined in the current document as the interpretation of life cycle assessment results within a geographical nature, has not gone unexplored entirely, yet its rise as a sub-method of life cycle assessment has been rather slow relative to other avenues of research (e.g., including the nutritional sciences within life cycle assessment). With this relative methodological stagnation as a motivating factor, our paper combines a process-based model, the Catchment Systems Model, with various life cycle impact assessments (ReCiPe, Centre for Environmental Studies and Environmental Product Declaration) to propose a simple, yet effective, approach for visualising the technically feasible efficacy of various on-farm intervention strategies. As water quality was the primary focus of this study, interventions reducing acidification and eutrophication potentials of both arable and livestock farm types in the Southeast of England were considered. The study site is an area with a marked range of agricultural practices in terms of intensity. All impacts to acidification potential and eutrophication potential are reported using a functional unit of 1ha. Percentage changes relative to baseline farm types, i.e., those without any interventions, arising from various mitigation strategies, are mapped using geographical information systems. This approach demonstrates visually how a spatially-orientated life cycle assessment could provide regional-specific information for farmers and policymakers to guide the restoration of certain waterbodies. A combination of multiple mitigation strategies was found to generate the greatest reductions in pollutant losses to water, but in terms of individual interventions, optimising farm-based machinery (acidification potential) and fertiliser application strategies (eutrophication potential) were found to have notable benefits.

A sustainable supply chain for a wellness tourism center considering discount and quality of service

Nowadays, the most successful and prominent wellness tourism centers are those that, consider the aspects of sustainable development, while providing memorable services with the best quality and reasonable prices. A wellness tourism center is seeking to meet the purposeful journey of wellness tourists by improving their mental, physical, and spiritual happiness. This paper presents a three-objective mathematical model to formulate the supply chain of services provided by a wellness tourism center. The purpose of this model is to establish a balance between sustainability aspects in this supply chain. The first objective seeks to maximize profits from the supply chain and the second and third objectives are to maximize customer satisfaction concerning environmental and social impacts. The proposed model includes quantitative parameters of operating costs, capacity increase cost, service capacity, and service demand. Due to the multi-objective nature of the model, the improved multi-choice goal programming method is used. Real data are collected from the Ardabil-Sarein wellness tourism center in Iran and used as a case study to validate and analyze the model. In collecting the dataset for the parameters, the three aspects of big data (3 V’s) are considered. Findings show that the model offers different types of discounts for various periods following the tourist demand. Additionally, the wellness tourism center can use the original cost to expand its range of services by offering different tours. Finally, the limitations and managerial suggestions are discussed.

Logistics Service Supply Chain Model

Logistics Service Supply Chain Model

Asset-light operation strategy for car-sharing model with vertical shareholding: financial leasing or instalment factoring

ABSTRACT Supply chain finance is an important way of realising the transformation of the asset-heavy operation mode in car-sharing services to an asset-light operation mode, by transforming the ownership cost into a variable cost. This study considers a service supply chain with vertical shareholding comprising a vehicle manufacturer and a car-sharing operator; further, it establishes financing decision-making models under financial leasing (FL) and instalment factoring finance (IFF) and explores the impact of profitability and shareholding ratios on FL and IFF. The results how that service profitability has a fundamental influence on financing decisions. The pooling effect and service satisfaction rate affect ownership costs and rental income, respectively. In turn, these factors jointly affect the choice of financing strategy. Moreover, there is a threshold of financing strategy choice related to the shareholding ratio: a large shareholding ratio means IFF is optimal, while when the ratio is low, FL is optimal. Finally, under certain conditions, a composite contract with revenue sharing and linear transfer payment for the optimal financing strategies can be adopted to improve supply chain performance. This study thus provides effective strategies for realising asset-light operation in car sharing by transforming ownership cost into variable cost.

Vulnerability prediction for secure healthcare supply chain service delivery

Healthcare organisations are constantly facing sophisticated cyberattacks due to the sensitivity and criticality of patient health care information and wide connectivity of medical devices. Such attacks can pose potential disruptions to critical services delivery. There are number of existing works that focus on using Machine Learning (ML) models for predicting vulnerability and exploitation but most of these works focused on parameterized values to predict severity and exploitability. This paper proposes a novel method that uses ontology axioms to define essential concepts related to the overall healthcare ecosystem and to ensure semantic consistency checking among such concepts. The application of ontology enables the formal specification and description of healthcare ecosystem and the key elements used in vulnerability assessment as a set of concepts. Such specification also strengthens the relationships that exist between healthcare-based and vulnerability assessment concepts, in addition to semantic definition and reasoning of the concepts. Our work also makes use of Machine Learning techniques to predict possible security vulnerabilities in health care supply chain services. The paper demonstrates the applicability of our work by using vulnerability datasets to predict the exploitation. The results show that the conceptualization of healthcare sector cybersecurity using an ontological approach provides mechanisms to better understand the correlation between the healthcare sector and the security domain, while the ML algorithms increase the accuracy of the vulnerability exploitability prediction. Our result shows that using Linear Regression, Decision Tree and Random Forest provided a reasonable result for predicting vulnerability exploitability.

Swarm Intelligence Technique for Supply Chain Market in Logistic Analytics Management

Supply chain management has become increasingly important as an academic subject due to globalization developments contributing to massive production-related benefits reallocation. The huge volume of data produced in the global economy means that new tools must be created to manage and evaluate the data and measure organizational performance worldwide. Smart technologies such as swarm intelligence and big data analytics can help get clear data of the location, condition, and environment of products and processes at any time, anywhere to make smart decisions and take corrective schedules that the supply chain can run more effectively. This study proposes the swarm intelligence modeling-based logistic analytics management (SIMLAM) in service supply chain market. A generalized structure for swarm intelligence implementation in supply chain management is suggested, which is advantageous to industry practitioners. Different deterministic methods practically fail due to the intrinsic computational complexity of the problem of higher dimensions.