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Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

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.

Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.

This paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.

This study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.

The results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.

Most of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.

This study aims to investigate a startup accelerator’s decisions toward exerting effort in an information acquisition process and selecting an information disclosure strategy. In particular, the authors are interested in examining which factors may cause the accelerator to report more or less accurate information, which will subsequently affect the investment decision and the outcome of the ventures. This study examines the impact of the equity share taken by the accelerator on the effort level being exerted in the information acquisition process, as well as the accelerator’s decision on the information disclosure regime.

The authors use mathematical models built upon well-established theoretical and practical concepts to analyze the research problems and derive the findings.

The authors show that when the accelerator takes a sufficiently large equity share from the entrepreneur in exchange for admitting the entrepreneur’s venture into the acceleration program, the accelerator is motivated to exert a significant level of effort to observe an accurate signal for the quality of the venture, and then disclose the information about the venture’s quality consistently with the observed signal (informative disclosure regime). On the other hand, if the accelerator takes a small equity share, it is optimal for her to exert no effort in the information acquisition process and simply adopt the basic disclosure regime, where the accelerator reports the quality of the venture based solely on the ex ante expected payoff of the venture, regardless of the observed signal.

The results indicate that an equity sharing scheme, which awards a sufficient amount of equity to the accelerator, can be an effective tool to help obtain accurate information about the quality of a startup venture and make a well-informed investment decision.

This research illustrates that the ownership stake of the accelerator can potentially indicate the accuracy of the information about the venture provided by the accelerator to outside investors. That is, when the stake held by the accelerator is large, the investors can conjecture that the information about the venture reported by the accelerator may be highly accurate and reliable. In contrast, if the accelerator holds a small stake, then it is likely that the information provided by the accelerator may not add any value to the publicly available information. These insights can guide investors (e.g. angle investors, venture capitalists, etc.) in making well-informed startup investment decisions.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This paper aims to review the literature extensively by analysing recent work and providing a guide for models, data sets and research findings.

This paper reviews the literature extensively by analysing recent work and providing a guide for models, data sets and research findings within the context of capital market imperfections. The authors further break down the literature into closer-in-nature categories for reader’s convenience and comprehension. Finally, the authors address gaps in the existing literature and propose government policies that can tone down the potential effect of credit rationing on employment.

This paper provides a map of the literature so as to help future researchers in the relevant literature and give a short insight of what has been explored so far.

This paper is original and is the result of a thorough review of an extensive literature.

The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.