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This study is aims to identify and categorize the perceived risks of Chinese tourists (from mainland China) traveling to Tehran. In addition, this study investigates the relationship between these risks tourists’ information seeking behavior.

This study investigates the relationship between these risks tourists’ information seeking behavior. The research also tries to model the relationship between the explored perceived risks and tourists’ information-seeking behavior. To collect data, a researcher-developed questionnaire containing 24 questions was designed based on a literature review. Before collecting the data, the validity and reliability of the questionnaire were reviewed and confirmed. To do study procedure, one essential question and two hypotheses, including exploratory factor analysis, stepwise regression and independent samples T-test, are used.

The results showed that Chinese tourists perceived health, physical, political, cultural, social and economic risks before their trip (with political risk being the most prominent). Also, the results indicate that the tourists have used different ways to collect information about Iran in general and Tehran in particular. Those travelers who perceived a higher risk were more likely to use the information sources that provide them with detailed and accurate information before traveling to Tehran.

This study provides valuable insights for destination managers and tourism marketers to attract Chinese tourists by considering their perceived risks and information-seeking behavior. It should be noted that this study is not without its own limitations. These limitations include (but are not limited to) the timeframe in which the data was collected (prior to the outbreak of COVID-19) and the destination (Tehran, Iran). Therefore, it is advised that future researchers study the perceived risks and information sources in other parts of the world.

The concept of perceived risk was used in Chinese tourists’ behavioral seeking to predict their future behavior following their perceptions. Thus, the findings of this study will be necessary to local governments and other destination organizations when building successful strategies.

This study explores the formation process of cognitive destination image among first-time Chinese millennial tourists visiting Iran.

Employing a comprehensive mixed-method exploratory approach, blending qualitative and quantitative methodologies, we aim to construct a conceptual model explaining the complex process of tourists’ cognitive destination image development. In the qualitative phase, interviews with 15 Chinese millennials unveiled key factors such as perceived behavioral control, perceived product quality, on-site involvement, engagement, and prior destination image as fundamental influencers of tourists’ cognitive destination image. Subsequently, in the quantitative phase, involving a questionnaire survey with 229 first-time Chinese travelers, we proposed a conceptual model to validate our primary findings.

The results highlight the emergence of on-travel cognitive image as a developmental concept originating from tourists' on-site participation and pre-existing perceptions of the destination. Moreover, we identified perceived behavioral control as the primary antecedent of millennials’ image formation, directly affecting the destination’s image development. Furthermore, increased involvement and engagement were found to diminish perceived behavioral control. Additionally, perceived product quality prompted millennials to engage more with cultural attractions and activities, enriching their in-situ image.

The findings offer valuable insights for destination managers, enabling them to construct tailored strategies to augment the cognitive destination image.

This study provides a novel understanding of the cognitive destination image formation process among Chinese millennial tourists, highlighting the crucial role of perceived behavioral control, involvement, engagement, and perceived product quality. These insights can guide destination managers in enhancing the overall tourist experience and destination appeal.

Prior research on the area of internet of things (IoT) development has primarily emphasized the overview descriptions and rarely investigated this area from a socio-technical standpoint. However, IoT development is a socio-technical ensemble, which requires analysis with a simultaneous focus on both technical and non-technical issues. Hence, this paper aims to analyze the development of IoT through the lens of the socio-technical system (STS) theory.

Having reviewed the STS theory, the key components of the IoT development are identified using prior literature review and semi-structured interviews with experts involved in the Iranian IoT development effort.

As a result, this paper provides insight into the key socio-technical issues in the IoT development classified under technology, tasks, structure and actors as four components of STS. Moreover, the close connections between the components are clarified.

This research is among the earliest studies, which use the STS theory to investigate the IoT development. The conducted socio-technical analysis of this study may assist the governments, industries and entrepreneurs as the chief stakeholders of IoT development to better align their actions with each other and achieve a balance between both technical and social sides.

The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays.

The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon.

The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed.

The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

Despite the availability of prior studies on the Internet of Things (IoT) development, they have largely focused on challenges associated with evolving IoT. Hence, identifying requirements for IoT development, as a multifaceted phenomenon, whereby the challenges would be tackled remains a less-explored valuable line of inquiry. The purpose of this paper is to present a holistic view of crucial building blocks of IoT development, in order to fill this gap.

This paper conducts empirical research using a grounded theory (GT), centering on semi-structured interviews with 25 experts involved in the Iranian IoT development effort. Data were analyzed by using MAXQDA software.

This study presents a conceptual framework of requirements for IoT development, consisting of 14 concepts and 5 categories. The findings reveal that strategic, interactive, institutional, market-oriented and information and communication technology (ICT) infrastructure requirements play a salient role in facilitating IoT development.

The findings of this study shed some light on the momentous aspects of IoT development. Practitioners including governmental policymakers, industry and private sectors could benefit from the policy recommendations offered in this study in terms of strategic viewpoint, legal issues, business perspective and technological readiness.

From the methodological aspect, the present research is among the first studies on utilizing GT for exploration of requirements for IoT development. From the theoretical perspective, a remarkable achievement of this study is to profoundly discover some less-explored concepts of IoT development such as commercialization, feasibility study, futurology and institutional aspects. Furthermore, findings of this study highlight the contribution of innovation systems theory for the IoT development area in terms of alignment of the emerged requirements for IoT development with the functions of this theory.

This study aims to examine the impact of the COVID-19 pandemic on the relationship between auditors’ work stress and client participation with audit quality (AQ).

This study is a descriptive-survey type and the data were collected through a questionnaire distributed online. The statistical population consisted of auditors working in audit firms in Iran and the sample was selected using a random sampling method. Structural equation modeling was used to analyze the data.

The findings of this study suggest that the COVID-19 pandemic exacerbated the negative relationship between auditors’ work stress and AQ. In addition, the results indicate that client participation in the audit process did not significantly impact AQ during the COVID-19 pandemic.

Given the global and widespread impact of the COVID-19 pandemic on individuals’ lives and work settings, this study provides an opportunity to explore the challenges auditors face concerning health protocols and their well-being during the pandemic, specifically within the context of Iran. The unique circumstances of the pandemic have placed additional pressure on auditors to navigate and address the challenges arising from COVID-19 in their workplaces. Although research on the effects of the pandemic on accounting and auditing is ongoing, this study contributes to the literature by expanding our understanding of the specific implications and circumstances faced by auditors during the COVID-19 outbreak.

This paper identifies the forces that drive digital adoption among SMEs from low and high-tech industries in Malaysia.

This research uses multiple case analyses based on data gathered by in-depth interviews with key representatives of 20 firms from low and high-tech industries in Malaysia.

The findings suggest that digital adoption among SMEs derives by four fundamental forces, which are sales, marketing, process improvement and product development.

This study employed qualitative research, but lack of geographic diversity limits the generalisability of the case findings. This study provides several suggestions to policymakers and technology suppliers on how to encourage adoption of digitalisation among SMEs.

This study proposes a model that presents the critical forces that drive digital adoption for export-oriented firms, thus enriching the knowledge in SME digitalisation literature.

This study aims to explore the perceptions of accountancy students on the use of technology, blended learning and flipped classroom in two emerging UK higher education institutions (HEIs).

The primary data for the study were collected using a questionnaire survey and descriptively analysed.

The findings revealed that there is some use of technology in terms of the Blackboard and PowerPoint presentations but blogs and wikis have very limited use. An aspect that does not seem to be integrated fully yet is the use of blended technology and a flipped classroom.

The study findings offer a picture of how technology, blended learning and the flipped classroom technique were utilised with accountancy students prior to the coronavirus disease 2019 (COVID-19) pandemic. This information is valuable for accounting educators and by extension to other aspects of business studies disciplines in providing a comparison between the pre-COVID-19 scenario and the current one and thus enabling an evaluation of advancement in the application of these teaching strategies as a result of the pressure imposed by social distancing. Such intelligence will facilitate the identification of areas where enhancing learning outcomes has been possible and point to opportunities for improved student experience.

Where COVID-19 brought about significant structural change in teaching and learning in the HE environment, this study represents a pre-COVID-19 consideration of student perceptions on blended learning and flipped classroom. This study thus has the potential to anchor future relevant studies that consider the post-COVID-19 environment.

The purpose of this paper is to develop an efficient and accurate mesh-less method to simulate free flows with continuous deformation in boundary positions.

A two-step pressure projection method in a Lagrangian form is used to solve the governing equations of mass and momentum conservation. In the first step, velocity field is calculated in which incompressibility is not enforced. In the second step, a pressure Poisson equation is applied to satisfy incompressibility conditions. The numerical proposed method is used for spatial discretization of the governing equations. Three benchmark-free surface problems, namely, dam break, solitary wave propagation and evolution of an elliptical bubble with available experimental results and analytical solutions, are used to test the accuracy of the proposed method. The results prove the accuracy of the method in simulating free surface problems.

The Voronoi diagram instead of kernel function summation can be used to estimate the particle or nodal volume concept in particle-based (mesh-less) methods for function approximation. This idea probably works well especially for highly irregular node distributions.

The continuous moving least squares shape functions are applied for function approximation, and the Voronoi diagram concept is also used to estimate region influence of computational nodal points or particle volumes. Combinations of these two concepts and finite differences formulation for first derivatives gives an accurate numerical model for Laplacian operator in the proposed method.

This study aims to introduce an efficient project buffer and resource management (PBRM) model for project resource leveling and project buffer sizing and controlling of project buffer consumption of a wind power plant project to achieve a more realistic project duration.

The methodology of this research consists of three main phases. In the first phase of the research methodology, resource leveling is done in the project and resource conflicts of activities are identified. In the second phase, the project critical chain is determined, and the appropriate size of the project buffer is specified. In the third phase of the methodology, buffer consumption is controlled and monitored during the project implementation. After using the PBRM method, the results of this project were compared with those of the previous projects.

According to the obtained results, it can be concluded that using PBRM model in this wind turbine project construction, the project duration became 25 per cent shorter than the scheduled duration and also 29 per cent shorter than average duration of previous similar projects.

One of the major problems with projects is that they are not completed according to schedule, and this creates time delays and losses in the implementation of projects. Today, as projects in the energy sector, especially renewable projects, are on the increase and also we are facing resource constraint in the implementation of projects, using scheduling techniques to minimize delays and obtain more realistic project duration is necessary.

This research was carried out in a wind farm project. In spite of the initial plan duration of 142 days and average duration of previous similar projects of 146 days, the project was completed in 113 days.

This paper introduces a practical project buffer and resource management model for project resource leveling, project buffer sizing and buffer consumption monitoring to reach a more realistic schedule in energy sector. This study adds to the literature by proposing the PBRM model in renewable energy sector.