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This paper aims to address a distributed assembly permutation flow-shop scheduling problem (DAPFSP) considering budget constraints and factory eligibility. The first stage of the considered production system is composed of several non-identical factories with different technology levels and so the factories' performance is different in terms of processing time and cost. The second stage is an assembly stage wherein there are some parallel work stations to assemble the ready parts into the products. The objective function is to minimize the maximum completion time of products (makespan).

First, the problem is formulated as mixed-integer linear programing (MIP) model. In view of the nondeterministic polynomial (NP)-hard nature, three approximate algorithms are adopted based on variable neighborhood search (VNS) and the Johnsons' rule to solve the problem on the practical scales. The proposed algorithms are applied to solve some test instances in different sizes.

Comparison result to mathematical model validates the performance accuracy and efficiency of three proposed methods. In addition, the result demonstrated that the proposed two-level self-adaptive variable neighborhood search (TLSAVNS) algorithm outperforms the other two proposed methods. Moreover, the proposed model highlighted the effects of budget constraints and factory eligibility on the makespan. Supplementary analysis was presented by adjusting different amounts of the budget for controlling the makespan and total expected costs. The proposed solution approach can provide proper alternatives for managers to make a trade-off in different various situations.

The problem of distributed assembly permutation flow-shop scheduling is traditionally studied considering identical factories. However, processing factories as an important element in the supply chain use different technology levels in the real world. The current paper is the first study that investigates that problem under non-identical factories condition. In addition, the impact of different technology levels is investigated in terms of operational costs, quality levels and processing times.

Industrial tourists can contribute to the local sites income. Apart from large and well-known industrial units, small industrial units can also introduce their products to the market by organizing tourism tours. This study aims to analyze an industrial tourism business network established in Isfahan, a large, industrial and historic city in central of Iran, as a case study.

Participants were managers and experts of organizations operated in the Industrial Tourism Network in Isfahan city. A sample of 30 participates was selected through purposive and snowball sampling approaches. Data was analyzed by qualitative content analysis and social network analysis using UCINET software.

Twenty-eight organizations participated in the Industrial Tourism Business Network of Isfahan. Macro indices of the network revealed that: density is relatively low; most of the relationships among network member organizations are reciprocal; transitivity is relatively weak indicating low network stability against environmental player; clustering is low, indicating a relatively low tendency of members to form different clusters. Micro indices indicated that in-degree and out-degree centralizations are low; overall centralization is poor. In addition, six actors were in the center and 22 actors were in the peripheral. Finally, the number of interactions of central organizations was triple than the peripheral organizations.

Limitations of this study include: The data obtained in this study only reflected the relationships among the actors studied during a specific period of time; this paper only focused on actors engaged in an industrial tourism network. Therefore, the sample might involve some bias. The results of the study contribute to our understanding of the role of networking in tourism destinations, particularly industrial sites.

According to the results, the authors may be able to advise firms operating in the tourism industry, particularly actors operate in industrial tourism, regarding how to increase their collaboration with both internal and external environment to achieve better performance.

To the best of the authors’ knowledge, this is the first paper that has addressed an industrial tourism business network.

The effectiveness of a message and its attributes have become important for digital media. This study aims to investigate how different elements of a website including both argument-oriented and emotional stimuli based on the elaboration likelihood model (ELM) can affect the issue involvement and change the attitude of the website visitors of a healthcare service provider.

The Ministry of Health and Education (MOHME) website was selected to explore how its content and design can persuade visitors. An online survey was conducted on 355 adults engaging in health protection behaviors during the COVID-19 pandemic.

Structural equation modeling (SEM) analysis showed that one design element, i.e. website navigation and one social cue, i.e. social connectedness, have positive impact on issue involvement, while social presence and website satisfaction have a negative effect on issue involvement because of the random fluctuation suppressor effect. In addition, prior knowledge significantly influenced the issue's involvement. Further, website satisfaction has impacted attitudes directly. There was no significant relationship between argument quality and issue involvement.

Previous works have studied health-related behaviors in offline contexts; however, the scholars have not focused on the individuals' persuasion using ELM regarding the healthcare services provided in online communities. The results of the current study have theoretical and practical implications for scholars, website designers and policymakers.

This study addresses the prevailing complexities and limitations in estimating and managing construction overhead costs (COCs) in the existing literature, with the purpose of enhancing the accuracy of cost performance indicators in construction project management.

An innovative approach is proposed, employing the activity-based costing (ABC) accounting method combined with building information modelling (BIM) to assign real overhead costs to project activities. This study, distinguished by its incorporation of a real case study, focuses on an administrative building with a four-story concrete structure. It establishes an automated method for evaluating project cost performance through the detailed analysis of earned value management (EVM) cost indicators derived from ABC results and BIM data.

The results show that the ABC integration improves the accuracy of cost performance indicators by over 9%, revealing the project's true cost index for the first time and demonstrating the substantial value of the approach in construction engineering and management.

The current study highlights a notable gap in the existing literature, addressing the challenges in onsite overhead cost estimation and offering a solution that incorporates the state-of-the-art techniques.

The proposed method has significant implications for project managers and practitioners, enabling better-informed decisions based on precise cost data, ultimately leading to enhanced project outcomes.

This research uniquely combines ABC and BIM, presenting a pioneering solution for the accurate estimation and management of COCs in construction projects, adding significant value to the current body of knowledge in this field.

This study aims to examine the effect of a combination of hybrid pin-fin patterns on a heat sink's performance using numerical techniques. Also, flow characteristics have been studied, such as secondary flow formation and flow-wall interaction.

In this study, the effect of hybrid arrangements of elliptical and hexagonal pin-fins with different distribution percentages on flow characteristics and performance evaluation criteria in laminar flow was investigated. Ansys-Fluent software solves the governing equations using the finite volume method. Also, the accuracy of obtained results was compared with the experimental results of other similar papers.

The results of this study highlighted that hybrid arrangements show higher overall performance than single pin-fin patterns. Among the hybrid arrangements, case 3 has the highest values of performance evaluation criteria, that is, 1.84 in Re = 900. The results revealed that, with the instantaneous change in the pattern from elliptic to hexagonal, the secondary flow increases in the cross-sectional area of the channels, and the maximum velocity in the cross-section of the channel increases. The important advantages of case 3 are its highest overall performance and a lower chip surface temperature of up to about 2% than other hybrid patterns.

Prior research has shown that in the single pin-fin pattern, the cooling power at the end of the heat sink decreases with increasing fluid temperature. Also, a review of previous studies showed that existing papers had not investigated hybrid pin-fin patterns by considering the effect of changing distribution percentages on overall performance, which is the aim of this paper.

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product.

To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated.

The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them.

This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English.

The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently.

No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.

The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.

In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.

This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.

This study addresses resilient mixed supply chain network design (SCND) and aims to minimize the expected total cost of the supply chain (SC) considering disruptions. The capacity of facilities is considered uncertain. In order to get closer to real-world situations, competition between SCs is considered.

A two-stage stochastic programming model is developed for designing the SC network. The location of facilities and selection of suppliers are considered first-stage decisions, and the determination of materials and products flows are second-stage decisions. Some resilience strategies are applied to mitigate the negative impacts of disruptions.

The results indicate that considering resilience and applying the related strategies are vitally important, and resilience strategies can significantly improve the SC objective and maintain market share. Also, it is confirmed that unrealistic decisions will be made without considering the competition.

This study contributes to the literature by proposing a novel mathematical model for the resilient mixed SCND problem. The other contribution is considering the chain-to-chain competition in collecting returned products and selling recycled products to other SCs in a mixed SC under disruptions. Also, a novel hybrid metaheuristic is developed to cope with the complexity of the model.

The concentration of women entrepreneurs on influential events such as the development of green entrepreneurship, which lead to the coordination and dynamic balance between economic and environmental goals, can create a bright future for businesses with sustainable and environmentally friendly architecture. The main purpose of this study is to provide a framework for the successful entry of women entrepreneurs into green entrepreneurship.

The present qualitative applied descriptive-analytical study was conducted on a population of women entrepreneurs working in green businesses. This population was obtained by the non-probability chain sampling method and an exploratory interview with the saturation of 12 individuals. Thematic analysis was used to analyze the findings.

The results revealed that creating shared value, inclusive social acceptance, multifaceted interactions and green dynamic bedding are effective in the entry of women entrepreneurs into green entrepreneurship in the form of “competitive empowerment” and “multiplied green synergy”. Thus, managers and planners should consider some factors, including shared value, social acceptance, inclusive acceptance, building green culture, knowledge flows, multiple participation, networking dimension, green marketing, competitiveness, creating platforms, green technologies and risk management.

This research tries to present a framework for the entry of women entrepreneurs into green entrepreneurship area.

Earlier, the consumption of products was based mainly on their utilitarian benefits, but at present, the love for nature has driven consumers towards products not harming the environment and society. Therefore, this paper aims to examine the influence of consumers' attitudes towards organic personal care products on brand love, brand trust, altruism and sustainable consumption behaviour. Furthermore, the study further examines the impact of sustainable consumption behaviour on continuous purchase intention using health consciousness as a moderator. Finally, the study validates Behavioural Reasoning Theory and the emotional affinity towards nature to understand the proposed claims.

The data were collected from 364 respondents from India. Only those respondents were included in the survey who had prior experience of using organic personal care products. This study used the structural equation modelling approach to test the conceptual model.

Results of the study confirmed the positive influence of consumer attitude on brand love, brand trust and altruism. Brand love and altruism had a significant impact on sustainable consumption behaviour. Health consciousness also emerged as a moderating variable between sustainable consumption behaviour and continuous intention. Interestingly, the brand trust had no impact on sustainable consumption behaviour. Furthermore, sustainable consumption behaviour had a significant impact on continuous intention.

The study is helpful to organic product companies, practitioners, academicians, environment protection agencies and market regulatory authorities as it gives fresh insight into the new collective relationship of consumer attitude with brand love, brand trust, altruism and sustainable consumption behaviour in case of organic personal care products.