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With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).

The current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.

The research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.

The proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

Drawing on information processing theory, the linkage between buffering and bridging and the ability on the part of procurement to resolve demand–supply imbalances is investigated, as well as contexts in which these strategies may be particularly useful or detrimental. Buffering may be achieved through demand change or redundancy, while bridging may be achieved by the means of collaboration or monitoring.

This study employs a hierarchical regression analysis of a survey of 150 Finnish and Swedish procurement and sales and operations planning professionals, each responding from the perspective of their own area of supply responsibility.

Both the demand change and redundancy varieties of buffering are associated with procurement's ability to resolve demand–supply imbalances without delivery disruptions, but not with cost-efficient resolution. Bridging is associated with the cost-efficient resolution of imbalances: while collaboration offers benefits, monitoring seems to make things worse. Dynamism diminishes, while the co-management of procurement in S&OP improves procurement's ability to resolve demand–supply imbalances. The most potent strategy for tackling problematic contexts appears to be buffering via demand change.

The results highlight the importance of procurement in the S&OP process and suggest tactical measures that can be taken to resolve and reduce the effects of supply and demand imbalances.

The results contribute to the procurement and S&OP literature by increasing knowledge regarding the role and integration of procurement to the crucial process of balancing demand and supply operations.

This study examines the relationship between policyholders’ psychographic characteristics and demand decisions for life insurance products in Uganda.

The study is based on a cross-sectional survey. Using a purposive sampling method, 389 questionnaires were administered to life insurance policyholders in the four geographical regions of Uganda. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the primary data, specifically to test the relationships between the dependent and independent variables.

The findings indicate a positive and significant influence of psychographic characteristics on demand decisions for life insurance products. In addition, the analysis indicates that the two first-order constructs of psychographic characteristics, namely price consciousness and consumer innovativeness, are positive and significant predictors of demand decisions for life insurance products. In contrast, the third first-order construct religious salience, exhibits a negative and nonsignificant effect on demand decisions for life insurance products.

For insurance practitioners, to influence demand decisions, they should emphasize premium-related appeals in their marketing messages (price consciousness) ignore product decisions based on religious beliefs and norms (religious salience). They should also ensure that insurance products are highly trustable and experiential (consumer innovativeness). For insurance policymakers, it offers an in-depth understanding of customer psychographic characteristics, which can be used to identify exploitative information embedded in certain marketing campaigns targeting specific psychographic characteristics, for better regulation.

The study provides a basis for understanding lifestyle and personality characteristics (psychographics), which may influence demand decisions for life insurance products in a developing country like Uganda, where the insurance industry is at an early stage of development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0440

The purpose of this study is to investigate the impact of greening and promotional effort dependent stochastic market demand on the remanufacturer's and the collector's profits when the quality of used products for remanufacturing is uncertain in a reverse supply chain.

The proposed model is developed to obtain optimal profits for the remanufacturer, the collector and the whole supply chain. Both the centralized and decentralized scenarios are considered. To motivate the collector through profit enhancement, the remanufacturer designs a cost-sharing contract. Through numerical examples and sensitivity analysis, the consequences of greenness and promotional effort on optimal profits are investigated.

The results show that the remanufacturer gets benefited from greening and promotional effort enhancement. However, a higher value of minimum acceptable quality level decreases the profits of the manufacturer and the collector. A cost-sharing contract coordinates the supply chain and improves the remanufacturer's and the collector's profits. Besides green innovation, remanufacturing mitigates the harmful effects of waste in the environment.

Two different viewpoints of remanufacturing are considered here – environmental sustainability and economic sustainability. This paper considers a reverse supply chain with a remanufacturer who remanufactures the used products collected by the collector. The quality of used products is uncertain, and customer demand is stochastic, green and promotional effort sensitive. These two types of uncertainty with green and promotional effort sensitive customer demand differs the current paper from the existing literature.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

This study investigates the impact of pre-IPO earnings management on investor demand in the Indian IPO market. It also examines whether earnings management by issuer firms affects IPO valuation, a topic that is underexplored in accounting research.

The study uses the data of 310 IPOs from India during the period 2000–2021. The association between pre-IPO earnings management with investor demand and valuation is tested using cross-sectional ordinary least squares regression models with heteroscedasticity-robust standard errors.

The study finds that the degree of pre-IPO earnings management impacts retail investor demand, measured as their over-subscription multiple. Pre-IPO earnings management is unrelated to institutional investor bidding. Further, this paper suggests no relation between pre-IPO earnings management and IPO valuation.

Future studies could explore various other forms of earnings management and their impact on investor demand and valuation.

The findings of this study will help the investors and regulators to understand the practice of earnings management among IPO firms and how it is related to IPO demand and valuation.

This study contributes to the existing literature on IPO-earnings management and investor demand by documenting that issuer firms engage in earnings management to influence investor demand, particularly retail investor demand. Analysis of IPO valuation reveals that earnings management is mostly unrelated to IPO valuation, contrary to the general perception in the literature.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

This paper applies a stakeholder salience theoretical framework to facilitate the understanding of the roles salient stakeholders can have in the integration of education for sustainable development, one of the important Sustainable Development Goals (SDGs), into Jordan’s university accounting education.

We used stakeholder salience theory to inform our study. This study adopted a qualitative research method. The study used semi-structured interviews to collect qualitative, open-ended data that explored the salient stakeholders’ thoughts, beliefs and feelings about their roles in influencing the integration of education for sustainable development into the Jordanian accounting curriculum.

The results indicate that education for sustainable development in accounting is important; however, most Jordanian salient stakeholders indicate their inability to integrate sustainable education into the accounting curriculum due to their lack of power to do so. The findings show that there is currently an inappropriate distribution of power, legitimacy and urgency amongst the salient stakeholders, who indicate that a progressive education solution is required in the critical area of education for sustainable development in accounting. This research indicates that a significant number of salient stakeholders would like the Jordanian government to provide power, legitimacy and urgency to enable accounting educators to become definite stakeholders as this will enable them to integrate sustainable education into the accounting curriculum.

The study is limited to Jordan only. The paper draws attention to the need for an appropriate distribution of power, legitimacy and urgency amongst salient stakeholders in Jordan.

This paper provides evidence that the salient stakeholders in this emerging economy want to make changes in their education system to address climate change concerns, an important SDG, through a better education curriculum for sustainable development in Jordanian universities.

Accounting educators should be given the power to make changes in the accounting curriculum, such as integrating education for sustainable development.

There is an inappropriate distribution of power, legitimacy and urgency amongst the Jordanian salient stakeholders and this imbalance hinders the integration of education for sustainable development into the accounting curriculum.