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In a logistics system the number of possible applications of qualitative and quantitative modelling efforts is practically infinite. The situations or problems which can be analysed range from micro operations (e.g., analysing alternative order picking systems) to macro planning issues (e.g., determining the number and location of warehouses to be employed in a future distribution system). This range of potential applications not only reflects the scope of the models (micro to macro) but it also incorporates another relevant dimension: planning. The planning axis is anchored at one end by operations models which are constructed to analyse daily operating practices. The other end of the continuum is represented by long range planning models. These models are used to aid logistics managers in their attempts to design systems to cope with the future. In many situations exact classification of individual models along these two dimensions is difficult. However, this categorisation is a useful framework within which to view the scope of the modelling discussed in this paper. This presentation will focus on the macro planning models that are being employed both in military and industrial logistics to aid the systems planner in his attempts to structure logistics systems for the future.

In the development processes of a product’s market life cycle, there are three phases of an enterprise’s innovation: new product development, production processes, and product management. In this article, the analyses of benefit and costs, value, and profit to companies are discussed in different stages. New logistics features that appear in an enterprise’s supply chain based on innovative modeling are discussed. Then a logistics model and its technical system based on the classified logistics center are established, which are appropriate for innovative modeling within an agile supply chain. Using the basic theory and techniques of ‘extenics’, the formal conception of innovative modeling-based manufacture in logistics is presented, and the matter-element models are established. Finally, a case study demonstrates the results.

This study aims to shed light on defining precisely variables of logistics costs model in Indonesia’s cement projects and generally other projects scientifically. The variables have previously so far been identified based on pragmatism and practical experience without rigorous scientific and empirical findings. The models are deeply awaited by every project practitioner, especially project controllers, in Indonesia.

Data for the period 2010–2018 of eight cement projects were taken in quarterly and tested with a statistical tool EVIEWS10 to develop a robust proposed model. Investigating models were done by literature studies and empirical studies, and the results had been examined by statistical tests to be determined as robust or not-robust models. The certain period taken due to the availability data of the cement projects in which after 2018 was unavailable because the cement product is overcapacity in Indonesia.

The model proposed is resulted by synthesizing logistics literature and empirical from the cement projects in which the model consists of foreign logistics costs, domestic manufacture, and domestic logistics costs as the best findings to develop logistics model for the cement projects with a-10 independent variable. It significantly found the variable of foreign logistics costs have taken higher portions in the model, and therefore must be prior carefully anticipated.

To guide investors to alert with several important variables of logistics in Indonesia. As education that to invest in Indonesia, the best logistics model must prior be known to anticipate further uncertainty.

This study is advanced applied research of logistics models developed by author for future possibility implementation in the sector beyond cement projects.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

The aim of this study is to provide a holistic analysis of all possible maritime business logistics processes related to import and export shipments in a fuzzy environment through a case study of a maritime logistics company based on the as-is and to-be models within business process management (BPM).

The analyses considered the following perspectives: (i) in the stage of the process identification, the definition of the problem was carried out; (ii) in the stage of the process discovery, ocean department was divided into ocean export/import operation departments; ocean export/import operation were divided into freight collect/prepaid operation processes; ocean export/import logistics activity groups were broken down into sub-activities for freight collect/prepaid operation; the logistics activity groups and their sub-activities were defined; each sub-activity as either operation or documentation process group was classified; the durations of sub-activities were evaluated by decision-makers (DMs) as fuzzy sets (FSs); the monthly total jobs activities were estimated by DMs as FSs; the applied to monthly jobs activities of total shipments were estimated by DMs as FSs; the durations of each sub-activities were aggregated; the duration of the logistics activity groups and the sub-activities for per job were calculated; the cumulative workload of logistics activity groups and sub-activities were calculated; the duration of sub-activities for per job as operation or documentation departments were calculated, (iii) in the stage of the process analysis, cumulative ocean export/import workload as operation or documentation for freight collect/prepaid were calculated; duration of activity groups and sub-activities for per job as operation or documentation were calculated; cumulative workload activity groups and sub-activities as operation or documentation were calculated, (iv) in the stage of the process redesign, cumulative workload, process cycle time as operation and documentation group and required labor force were calculated; the process cycle time of the theoretical, the as-is model and the to-be model were calculated: (i) the theoretical minimum process cycle time without resource were calculated by the critical path method (CPM), (ii) the process cycle time of the as-is model perspective with the 1 person resource constraint and (iii) the process cycle time of the to-be model perspective with the 2-person resource constraint were calculated by the resource constrained project scheduling problem (RCPSP) method.

The methodology for analyzing the ocean department operation process was successfully implemented in a real-life case study. It is observed that the results of the to-be model can be applicable for the company. The BPM-proposed methodology is applicable for the maritime logistics industry in the present study; however, it can be applied to other companies in maritime logistics as well as other industries.

This study contributes to research using BPM methodology in maritime logistics. This is the first study the logistics process analyses were carried out in terms of including all operation processes for a company. All processes were analyzed by using BPM methodology in maritime logistics. This study demonstrated the application of the BPM as-is and to-be models to maritime logistics. The as-is and the to-be models of the BPM methodology were applied in maritime logistics.

This methodology applied in this study can enable organizations operating in the time-urgent maritime logistics sector to manage their logistics processes more efficiently, increase customer satisfaction, reduce the risks of customer loss due to poor operational performance and increase profits in the long term. Through the use of these methodologies utilizing FSs, the CPM and the RCPSP methods, this study is expected to make contributions to the BPM literature and provide original insights into the field. Furthermore, this study will undertake a comprehensive analysis of maritime logistics with respect to BPM to deliver noteworthy contributions to the maritime logistics literature and provide original perspectives into the field.

This paper investigates how the channel leadership strategies develop a post-coronavirus disease (COVID-19) resilient agri-supply chain, which reduces supplier and retailer's price loss and enhances the logistics service quality level considering logistics outsourcing of agri-product especially for the rapidly changing market condition.

Based on the classical leadership theory, two channel leadership strategies, i.e. LPL and SL, are considered. The proposed framework first derives the equilibrium price and service quality level decision among the supplier, the logistics provider and the retailer. Then it compares both leadership strategies in terms of the equilibrium prices and service quality theoretically. This article also presents a case study of Arabian dates pricing and supply chain to test the theoretically derived propositions.

Selection of suitable leadership strategy is a critical factor for profit maximization of the supply chain drivers and proper optimization of equilibrium price and service quality. Here, the product's quality and the market's socio-economic condition play an important role in selecting a suitable leadership strategy. A random transformation of the physical market to an e-commerce portal creates a wide variation of the market's socio-economic parameters, affecting the equilibrium pricing and the logistics provider's service quality.

This study proposes a post-COVID-19 resilient agri-supply chain framework considering price and quality-dependent stochastic market demand, incorporating a wide range of socio-economic factors in the model to counteract the effect of rapid behavior change of agri-market due to COVID-19 norms. This research examines the effect of different channel leadership strategies to facilitate suitable decisions on prices and service quality and retrieve the profit of the supplier, retailer and logistics provider. The future models can incorporate competitiveness in logistics outsourcing, fourth-party logistics (4PL) and contract farming in the agri-supply chain. Each of the extensions can open avenues in different directions.

As the post-COVID-19 market and the customer behavior is randomly changing, and the traditional market is rapidly converting into supermarkets and e-commerce portals, this paper examines the model with a wide variety of e-commerce portals with multi-variation of product. It is conclusive that the product's quality and the market's socio-economic behavior significantly impact the equilibrium decision. The drivers of the supply chain must take them into account before choosing a particular channel leadership strategy.

This study considers a multi-product and multi-market (e-commerce) model by integrating a wide variety of products and the market's socio-economic parameters. The model is tested in a price and quality-dependent stochastic market condition, contributing to the literature by reconciling two different channel leadership strategies into the global logistics of fresh agri-product.

The automotive industry has been studied extensively, but few studies focus on outbound logistics in automotive supply chains, or on the logistics service provider’s (LSP’s) point of view. Furthermore, there is hardly any research on service model innovation in LSPs. The purpose of this paper is to narrow these research gaps.

The analysis is based on a single-case study – an LSP that specializes in services for the automotive industry. The paper examines the company’s service models and their development over time.

The findings show how the case company has moved towards multifaceted service models through a number of radical and incremental innovations. Moreover, it has used the same methods in developing all its new service models, and has applied modularity principles in service innovation to achieve better process efficiency and service effectiveness.

The rather narrow focus of this study – automotive logistics in a specific area – decreases the generalizability of the findings beyond this context. However, the single-case approach offers in-depth insights, and the analytical frameworks developed herein for service models is applicable in other contexts.

The analysis may help LSPs and service companies in their service design and development. The use of modularity principles makes it easier to offer mass-customized services and to develop efficient processes.

This study narrows a research gap in examining outbound logistics services in the automotive supply chain and focussing on the LSP’s perspective.

This work aims to combine the perspectives of logistics‐service providers (LSPs) and small and medium‐sized enterprises (SME) in the development of value‐added logistics services. The purpose was to create a theory‐based and initially tested framework that could help both service providers and SMEs identify new opportunities for developing their logistics.

The research followed design‐science methodology and was carried out via semi‐structured interviews within the case company (a large Finnish LSP), its customers, and experts from the area of logistics services. Data on companies offering value‐added logistics services were also used in the research. The focus of the research was on advanced value‐added logistics services.

The paper presents a framework for categorizing logistics services for SMEs and proposes new logistics‐service models for SME customers. Altogether, three service models are proposed to bridge the gap between LSP and SME customers. In particular, the consulting‐oriented approach seemed to be appropriate for the SMEs. The other two models, 3PL with planning and Outsourced Chief Logistics Officer, require more effort from both parties.

The paper presents a theoretical framework for categorizing logistics services and discusses the strategic options for an LSP to expand its service portfolio. However, further empirical research related to logistics‐service design is needed to develop the framework further and to improve its external validity.

This work offers insights that support LSPs to develop their service offerings to better match the needs of SMEs, and also allow managers of SMEs to better utilize the available LSP competence and services.

The existing research in the area of value‐added logistics services has mainly focused on either the customer perspective or the service‐provider perspective. The dyad combining these perspectives has been largely neglected. Furthermore, studies in this area have been on large enterprises as opposed to SMEs. This work fills this gap by designing value‐added logistics‐service models that combine SME needs with LSP capabilities.

This study aims to assist the project manager in minimising the material logistics cost of road project by planning the optimal movement of aggregate across three stages of supply chain: sourcing, processing and distribution.

The paper conceptualises the raw material consumption in a road project as a logistics network distribution problem. A linear programming (LP) formulation is constructed with appropriate decision variables by integrating the three stages of material movement. The series of LP scenarios are solved using an LP solver to decide the optimal movement of the aggregate to be consumed in different layers of road segments.

The results obtained from the model show that planning material logistics of an entire road project using optimisation provides substantial saving in logistics costs than using common sense. Further, the magnitude of cost saving improves as the complexity of the model increases in term of enormous feasible options.

The model shown in this paper may serve as a basis for planning the logistics of raw materials consumed in the road projects. The small improvement in material flows by optimising supply chain shows sensible cost benefit to the project manager and hence control and monitor the overall cost and activities of the project. The output of the model is also expected to help the project team as an input in the decision-making processes such as appropriate material sourcing contract, capacity assessment of material processing facility and transportation planning.

While the optimisation models are widely used and popular among the many industrial applications, this research shows distinct application of such a model in managing the logistics of the road construction project.