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This study aims to develop a framework to identify the drivers underpinning food tourists' behavioral intentions (BIs). This framework centers on examining how local food consumption value (TLFCV), local food experiential value (TLFEV) and social media influencers (SMIs) impact upon tourists’ attitudes toward local food (ATLF) and food destination image (FDI). The impact of ATLF and FDI on tourists’ BIs is also examined.

PLS-SEM was used to test the hypothesized relationships using survey responses from 379 tourists visiting Rasht, Iran.

The results demonstrate that TLFCV, TLFEV and SMIs can be used to populate a theoretical framework for predicting and understanding the factors influencing tourists’ ATLF and FDI. Specifically, positive ATLF and FDI stimulated positive BIs (e.g., intending to recommend Iranian food to others and intending to revisit Iran in future for culinary tourism purposes).

The findings provide managers and practitioners within the culinary tourism industry with suggestions for how best to strategically market their offerings to increase inbound food tourism.

This study is one of the first to empirically evaluate the drivers of food tourists' BIs, presenting a newly developed model for deployment in future research. Originality is also established by simultaneously investigating TLFCV and TLFEV within the context of food tourism.

The primary objective of the present study was to design and develop a model to identify the antecedents and consequences of user satisfaction with digital libraries.

The theoretical framework of this study was based on information system success theory, technology acceptance model (TAM), media affinity theory, satisfaction-loyalty theory and engagement theory. In so doing, eight hypothesized relationships were formulated to develop the conceptual model. The study approach was quantitative. Using simple random sampling technique, a total of 409 Iranian students participated in the study and responded to the survey. Descriptive and inferential data analysis was also performed using SPSS and SmartPLS3 software.

The results showed that the generic usability of digital library and the quality of digital resources could be used as a functional theoretical framework to predict and understand the factors contributing to user satisfaction in the domain of digital library. Increasing user satisfaction with digital library may have implications including recommending the digital library to others, the digital library reusing as well as the digital library engaging and integrating with them. It should be noted that system quality, service quality, and information quality are important factors in the formation of perceived usefulness, perceived ease of use, and digital libraries' affinity.

This study is the first attempt to empirically evaluate the antecedents and consequences of the user satisfaction with digital library presenting a new model. The model presented in this study can be used in future research as well. Also, this study has eloquently expanded the theories of user satisfaction with digital libraries.

The study's main objective is to evaluate the morphological developments in the characteristics of the spatial configurations of the residential layouts in Kerman, Iran, in examining the impact on the level of visual privacy through the spectrum of permeability and wayfinding in space syntax analysis.

In this paper, plan graph analysis is used to measure the syntactic properties of seven topological residential architecture plans in Kerman, Iran, built from the 1970s to 2010s. The methodology involves the development of mathematical measurements to signify permeability and simulation of visibility graph analysis (VGA) to indicate wayfinding.

The findings reveal the residential layouts of Iranian houses tend to be less integrated over decades of design development from the 1970s to 2010s. Reduction in spatial integration corresponds to increase segregation allowing for enhanced visual privacy. The study underpins that, even with the constraints in the scale of the house and reduction in the number of nodes, as evident in the design of the modern residential layout, the efficient level of visual privacy is still achievable with regards to the standards demanded by the local culture.

The study examines the development in residential spatial configuration and building scale on visual privacy through a proposed methodology based on the level of permeability and wayfinding measured as a combined effect using the space syntax analysis and visual accessibility.

This study aimed to present a model for open-data management for developing innovative information flow in Iranian knowledge-based companies (businesses).

The method was mixed (qualitative-quantitative) and data collection tools were interview and questionnaire. The qualitative part was done to identify the influential components in open data management (ecosystem) using the grounded theory method. A questionnaire was developed based on the results of the qualitative section and the theoretical foundations, and the quantitative section was conducted by analytical survey method and the model was extracted using factor analysis and the integration of the qualitative section.

Seven categories of entrepreneurial incentives, sustainable value, innovative features, challenges and barriers, actors, business model and requirements are the main categories that should be considered in open data management (ecosystem) with all categories of research have a significant relationship with open data management.

The study focused on open data management from an innovation paradigm perspective and its role in developing innovative information flow. The study aimed to identify the key components of the open data ecosystem, open-data value creation, and the need to use the “open data” approach to develop data-driven and knowledge-based businesses in Iran–an emerging approach largely ignored.

The purpose of this study is to evaluate two supply chain resilience key elements of vulnerability and capability in the automotive industry.

We propose a fuzzy approach for statistical hypothesis testing and analyze two research hypotheses by synthesizing the results of a questionnaire given to 44 companies in the Iranian automotive industry.

The results indicate that the automotive industry in Iran should: (1) resist five elements of vulnerability, i.e. “external pressures,” “sensitivity,” “connectivity,” “supplier/customer disruptions,” and “resource limits,” and (2) embrace nine elements of capability, i.e. “flexibility in order fulfillment,” “capacity,” “efficiency,” “visibility,” “adaptability,” “recovery,” “dispersion,” “organization,” “market position” and “security” to achieve greater resiliency elasticity in the supply chain.

This is the first study on the supply chain resilience vulnerabilities and capabilities in the Iranian automotive industry.