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This study aims to determine the optimal value of concession period length in combination with capital structure in build–operate–transfer (BOT) contracts, based on direct negotiation procurement and considering the conflicting financial interests of different parties involved in the project.

The financial model of a BOT project is developed considering all the influencing factors. Then, fuzzy set theory is used to take into account the existing risks and uncertainties. Bilateral bargaining game based on alternating-offers protocol is applied between the government and the sponsor to divide project financial benefit considering the lender’s requirements. Finally, concession period and equity level will be determined simultaneously according to the sponsor’s and government’s share of project financial benefit and the lender’s requirements.

The proposed model is implemented on a real case study, and a fair and efficient agreement on concession period length and capital structure is achieved between the government and the sponsor considering the lender’s requirements. It is revealed that being the first proposer in the bargaining process will affect the concession period length; however, it will not affect the equity level. Moreover, it is shown that considering income tax as a part of government’s financial benefit increases the length of concession period.

The presented model concentrates on direct negotiation procurement in BOT projects where the sponsor and government bargain on dividing financial benefits of project. It is assumed that the product/service price is determined before according to market analysis or users’ affordability. All the revenue of project during concession period is assumed to belong to the sponsor.

The proposed model provides a practical tool to aid BOT participants to reach a fair and efficient agreement on concession period and capital structure. This could prevent failing or prolonging the negotiation and costly renegotiation.

By investigation of previous studies, it is revealed that none of them can determine the optimal value of concession period length and capital structure simultaneously considering the BOT negotiation process and different financial interests of parties involved in the project. The proposed model presents a new approach to determine the financial variables considering the conflicting interests of involved parties. The other novelty aspects of the presented model are as follows: introducing a new approach for calculating the sponsor and the government’s share of project financial benefit that will affect the determination of the concession period length and considering the effect of existing risks and uncertainties on final agreement between the involved parties using fuzzy set theory.

Human or machine, which one is more intelligent and powerful for performing computing and processing tasks? Over the years, researchers and scientists have spent significant amounts of money and effort to answer this question. Nonetheless, despite some outstanding achievements, replacing humans in the intellectual tasks is not yet a reality. Instead, to compensate for the weakness of machines in some (mostly cognitive) tasks, the idea of putting human in the loop has been introduced and widely accepted. In this paper, the notion of collective hybrid intelligence as a new computing framework and comprehensive.

According to the extensive acceptance and efficiency of crowdsourcing, hybrid intelligence and distributed computing concepts, the authors have come up with the (complementary) idea of collective hybrid intelligence. In this regard, besides providing a brief review of the efforts made in the related contexts, conceptual foundations and building blocks of the proposed framework are delineated. Moreover, some discussion on architectural and realization issues are presented.

The paper describes the conceptual architecture, workflow and schematic representation of a new hybrid computing concept. Moreover, by introducing three sample scenarios, its benefits, requirements, practical roadmap and architectural notes are explained.

The major contribution of this work is introducing the conceptual foundations to combine and integrate collective intelligence of humans and machines to achieve higher efficiency and (computing) performance. To the best of the authors’ knowledge, this the first study in which such a blessing integration is considered. Therefore, it is believed that the proposed computing concept could inspire researchers toward realizing such unprecedented possibilities in practical and theoretical contexts.

The halal food market is a large and fast-growing market. To maintain and boost the growth of the halal food industry, scholars have attempted to understand the behaviour of Muslims and non-Muslims towards halal food. To advance understating of previous studies on behaviour towards halal food and shedding light on future studies, this study aims to systematically review the literature.

A sample of 985 peer-reviewed papers was extracted from Scopus and Web of Science databases. A total of 96 articles related to customers' behaviour towards halal food by reviewing the titles, abstracts and contents of the extracted articles were identified and reviewed.

This study illustrates: (i) various research designs and methodology used in halal food context, (ii) theories that researchers used to explain customer behaviour towards halal food, (iii) most tested behaviours and (iv) determinants of customer behaviour towards halal food.

The findings provide deep insights into the current state of halal food literature. This paper highlights many gaps in the literature and suggests directions for future studies to advance the understanding of customer behaviour towards halal food. This study will help researchers to identify the new dimensions of research and contribute to the literature.