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This article develops an innovative multidisciplinary conceptual framework in the field of refugee entrepreneurship by combining the theory of mixed embeddedness with the concepts of intersectionality and agency. Focusing on the phenomenon of refugee entrepreneurship, this conceptual framework addresses the following questions: how is entrepreneurship informed by the various intersectional positions of refugees? And how do refugees exert their agency based on these intersecting identities?

By revising the mixed embeddedness approach and combining it with an intersectional approach, this study aims to develop a multidimensional conceptual framework.

This research illustrates how the intersectional positions of refugees impact their entrepreneurial motivations, resources and strategies. The authors' findings show that refugee entrepreneurship not only contributes to the economic independence of refugees in new societies but also creates opportunities for refugees to exert their agency.

This conceptual framework can be applied in empirical research and accordingly contributes to refugee entrepreneurship studies and intersectionality theory.

This study investigates the sustainability models of non-profit and hybrid organizations, which aim to balance economic, social and environmental objectives. The research introduces the Sustainability Model Canvas to analyze these organizations and identify common patterns, unique characteristics and managerial insights to balance the triple bottom line.

The research utilizes the Sustainability Model Canvas to examine the sustainability models of 200 non-profit and hybrid organizations. Data were collected from secondary sources, including articles, reports and websites. The analysis was conducted using the activity system theoretical framework, which helped to identify design elements and themes within the business models of the studied organizations.

The study reveals four primary sustainability model patterns: donated income, earned income, public income and auto-generated income. An additional mixed approach pattern is identified, combining elements from the four primary patterns. The research highlights the parallels between these sustainability models and multi-sided platform business models, offering managerial suggestions for leveraging these patterns to achieve sustainability.

The study is based on secondary data, which may limit the depth of insights compared to primary data collection. At the same time, the chance to consider hybrid organization through multi-sided platform lenses provides relevant contributions to both the literature streams.

The identified sustainability model patterns and managerial suggestions can serve as blueprints for non-profit and hybrid organizations aiming to design or innovate their sustainability models. The Sustainability Model Canvas offers a practical tool for organizations to visualize and balance their triple bottom line objectives.

The research underscores the importance of integrating social and environmental considerations into business models, promoting a holistic approach to sustainability that can lead to broader social and environmental benefits.

This research contributes to the business model literature by extending the focus beyond traditional profit-oriented organizations to include non-profit and hybrid organizations. The introduction of the Sustainability Model Canvas provides a new tool for designing and analyzing sustainability-oriented business models. The study also suggests considering sustainability models as multi-sided platforms, offering new insights for both academic and practical applications.

Owing to the finite nature of the boundary of the line (BOL), the conventional method, involving the strong matching of single-variety parts with storage locations at the periphery of the line, proves insufficient for mixed-model assembly lines (MMAL). Consequently, this paper aims to introduce a material distribution scheduling problem considering the shared storage area (MDSPSSA). To address the inherent trade-off requirement of achieving both just-in-time efficiency and energy savings, a mathematical model is developed with the bi-objectives of minimizing line-side inventory and energy consumption.

A nondominated and multipopulation multiobjective grasshopper optimization algorithm (NM-MOGOA) is proposed to address the medium-to-large-scale problem associated with MDSPSSA. This algorithm combines elements from the grasshopper optimization algorithm and the nondominated sorting genetic algorithm-II. The multipopulation and coevolutionary strategy, chaotic mapping and two further optimization operators are used to enhance the overall solution quality.

Finally, the algorithm performance is evaluated by comparing NM-MOGOA with multi-objective grey wolf optimizer, multiobjective equilibrium optimizer and multi-objective atomic orbital search. The experimental findings substantiate the efficacy of NM-MOGOA, demonstrating its promise as a robust solution when confronted with the challenges posed by the MDSPSSA in MMALs.

The material distribution system devised in this paper takes into account the establishment of shared material storage areas between adjacent workstations. It permits the undifferentiated storage of various part types in fixed BOL areas. Concurrently, the innovative NM-MOGOA algorithm serves as the core of the system, supporting the formulation of scheduling plans.

The purpose of this study is to systematically analyze the wear of cylindrical needle bearings in rotary vector reducers under temperature rise and identify the influencing factors.

Based on the dynamic characteristics of the RV-20E reducer, the time-varying contact force of the cylindrical needle bearing and the entrainment speed of the inner and outer raceways were calculated. A mixed elastohydrodynamic lubrication model of the needle bearing, considering friction and temperature rise, was established using a dynamic rough tooth surface model. The model solved for the oil film thickness, contact stress and wear conditions of the bearing raceway contact area. The effects of the number of rolling needles, the diameter of rolling needles and surface strength on the wear characteristics were analyzed.

The results of this study show that the oil film thickness, oil film pressure and surface scratches of cylindrical needle bearings exhibit an uneven, patchy distribution under the combined effects of friction and temperature rise. When the radius of the rolling needle is less than 1.44 mm, inner ring wear is less than outer ring wear. Conversely, when the radius exceeds 1.44 mm, inner ring wear is greater. The optimal rolling needle radius is 1.6 mm. Increasing the number of rolling needles and enhancing the yield strength of the contact surface significantly extend bearing life.

This study provides valuable recommendations for optimizing bearing structural parameters and material characteristics in the design of rotary vector reducers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0242/

The study estimates the willingness to pay for organic oranges and identifies its influencing factors among consumers in the Mekong Delta, Vietnam.

The study used survey data from 413 households in the Mekong Delta from March 2022 to July 2022. The choice experiment (CE) and contingent valuation method (CVM) were employed to analyze consumers’ willingness to pay (WTP). STATA 17 software was used to analyze research data in the logit model and mixed logit model.

The research results from the CVM approach show that a number of demographic characteristics have a direct impact on WTP, such as education, educational attainment, family size, the presence of children and the elderly in the household, food safety and environmental awareness. The CE model shows product attributes that influence consumers’ WTP, such as country of origin, traceability, quality grade, organic certification, ecolabel and organic content. Both approaches show that price is the main barrier to organic orange consumption.

The study surveyed four large cities in four provinces representing the Mekong Delta region.

Our study helps administrators have a deeper insight into consumer preferences and behavior, specifically the factors that affect consumers' WTP, an important indicator of demand for the success of manufacturers and marketers in developing as well as improving marketing strategies. Knowledge of a product’s WTP on behalf of (potential) customers plays an important role in many areas of marketing management, such as pricing decisions or new product development.

Furthermore, this understanding will inform policymakers about the future of agricultural markets in Vietnam and help them better prepare for the making of sustainable agricultural policies. Develop organic agriculture to both protect human health, protect the living environment and protect the soil from degradation, ensuring sustainable agricultural production. This is also one of the measures to help people stay away from diseases to limit the social burden.

The study confirms that both CVM and CE models can be used to estimate WTP. However, CVM fits the overall WTP estimate, while CE is more appropriate when estimating WTP for individual scenarios through combining attributes with different levels.

This study aims to explore the intricate relationship between uncertainty indicators and volatility of commodity futures, with a specific focus on agriculture and energy sectors.

The authors analyse the volatility of Indian agriculture and energy futures using the GARCH-MIDAS model, taking into account different types of uncertainty factors. The evaluation of out-sample predictive capability involves the application of out-sample R-squared test and computation of various loss functions.

The research outcomes underscore the significant impact of diverse uncertainty factors such as domestic economic policy uncertainty (EPU), global EPU (GEPU), US EPU and geopolitical risk (GPR) on long-run volatility of Indian energy and agriculture (agri) futures. Additionally, the study demonstrates that GPR exhibits superior predictive capability for crude oil futures volatility, while domestic EPU stands out as an effective predictor for agri futures, particularly castor seed and guar gum.

The study offers practical implications for market participants and policymakers to adopt a comprehensive perspective, incorporating diverse uncertainty factors, for informed decision-making and effective risk management in commodity markets.

The research makes an inaugural attempt to examine the impact of domestic and global uncertainty indicators on modelling and predicting volatility in energy and agri futures. The distinctive feature of considering an emerging market also adds a novel dimension to the research landscape.

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 objective of this study is to explore the structural attributes of the pharmaceutical industry before the onset of the COVID-19 pandemic by examining the relationship between inventory and firm performance and developing a taxonomy of pharmaceutical firms based on the earns-turns matrix.

This study examines the inventory–firm performance linkage, considering both total inventory and its discrete inventory components in pharmaceutical firms. In addition, this research develops a new taxonomy of pharmaceutical firms based on the earns-turns matrix. A large panel dataset of firms in the US pharmaceutical industry was collected for the period 2000–2019.

The results reveal that strategic groups identified based on this taxonomy show different levels of profitability and inventory turns in the earns-turns matrix. Most pharmaceutical firms moved from the low-right to the top-left section in the earns-turns matrix, indicating that these firms have generally pursued profitability rather than effective inventory management.

This study explores the structural attributes of the pharmaceutical industry using the earns-turns matrix. This two-dimensional analysis may not, however, capture the full complexity of inventory–firm performance dynamics.

The mapping of strategic groups on the earns-turns matrix provides a useful tool for visual representations of the dynamics of strategic groups in terms of financial performance and inventory management performance. Practitioners can use the earns-turns matrix to benchmark their firm's position against their competitors.

This study broadens the scope of operations management research by introducing the earns-turns matrix as an empirical validation tool for operational and strategic management theories. This study emphasizes the effectiveness of the earns-turns matrix in analyzing strategic groups of pharmaceutical firms.

The purpose of this paper is to provide an overview of the computational progress in the development of hydrogen-fired gas turbines. This review aims to identify suitable combustion models, appropriate NO_x chemistry mechanisms and NO_x emission levels for effective utilization of hydrogen as an alternative fuel in gas turbines.

Hydrogen is recognized as a potential alternative fuel for achieving exceptionally low emissions in gas turbines. The developments in conventional, trapped vortex combustor and micromix combustors are discussed, along with various computational models aimed at accurately predicting combustion and emission characteristics. The results of numerical simulations were then discussed with emphasis on their role in optimizing the combustor geometry.

Computational studies that were used to optimize the combustor geometry to reduce NO_x emissions and the flashback phenomenon are discussed. To retrofit existing gas turbines for hydrogen fuel, minor modifications that are required were discussed by analyzing extensive literature. The influence of key design and geometrical parameters on NO_x emissions and the appropriate selection of combustion models for numerical simulations in optimizing various combustion systems are elaborated.

The review emphasizes the computational studies in the progress of hydrogen-fired gas turbine developments. The previous reviews were primarily focused on the combustion technologies for hydrogen-fired gas turbines. This comprehensive review focuses on the key design parameters, flame structure, selection of combustion models, combustion efficiency improvement and impact of parametric studies on NO_x formation of various combustion systems, in particular hydrogen combustion for gas turbine applications.

The role of procurement managers is crucial for diffusing sustainability throughout the supply chain. Whether or not they are willing to pay for sustainability is an important and not yet fully understood question. The authors examine antecedents and consequences of their willingness to pay (WTP) for sustainability.

The authors develop a multi-level framework to examine the WTP for sustainability in a B2B context. The authors test this multi-level framework with 372 procurement managers from multiple sectors and countries using partial least squares structural equation modeling.

The authors find that individual values of procurement managers and institutional pressures directly, while ethical organizational culture indirectly influence WTP for sustainability. Functional and cognitive competencies of procurement managers improve the sustainability of procurement, but not WTP for sustainability. Importantly, WTP for sustainability directly influences the performance of the procurement function which in turn is positively associated with increased organizational performance.

The study, examining the interplay between individual, organizational and contextual factors, provides empirical evidence on the pivotal role of procurement managers in diffusing sustainability throughout the supply chain. The findings of the study, on the one hand, contribute to the literature on operations management and sustainability, and on the other hand, guide policy and managerial actions.