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The paper aims to report a fire test conducted on a three-dimensional frame in order to investigate the behaviour of bare steel flush end-plate connections with relatively low thickness at elevated temperatures.

A half-scale model was fabricated and exposed to modified (scaled) ISO 834 heating curve using a semi-open furnace. The maximum temperature inside the furnace reached 1,026 °C.

The rotations of connections are reported and compared with those of a previous study on an exactly the same model with thick end-plates. Various modes of failure such as local buckling of the beams flanges and lateral-torsional buckling of beams were observed during the test. Finally, the structure collapsed after 29 min of heating due to the fracture of weld between one of the beams and one of its attached end-plates whilst the other beam had undergone a maximum deflection of 35 cm (≈ 1/6 span length). Other observed failure modes included bolt fracture, bolt thread stripping and large inelastic deformation of the end-plates.

Although the adoption of thin end-plates increased the rotational capacity of the connections, it did not improve the robustness of the structure under fire conditions.

The purpose of this paper is to present a vision-based method for the kinematic calibration of a six-degrees-of-freedom parallel robot named Hexa using only one Universal Serial Bus (USB) camera and a chess pattern installed on the robot's mobile platform. Such an approach avoids using any internal sensors or complex three-dimensional measurement systems to obtain the pose (position/orientation) of the robot's end-effector or the joint coordinates.

The setup of the proposed method is very simple; only one USB camera connected to a laptop computer is needed and no contact with the robot is necessary during the calibration procedure. For camera modeling, a pinhole model is used; it is then modified by considering some distortion coefficients. Intrinsic and extrinsic parameters and the distortion coefficients are found by an offline minimization algorithm. The chess pattern makes image corner detection very straightforward; this detection leads to finding the camera and then the kinematic parameters. To carry out the calibration procedure, several trajectories are run (the results of two of them are presented here) and sufficient specifications of the poses (positions/orientations) are calculated to find the kinematic parameters of the robot. Experimental results obtained when applying the calibration procedure on a Hexa parallel robot show that vision-based kinematic calibration yields enhanced and efficient positioning accuracy. After successful calibration and addition of an appropriate control scheme, the robot has been considered as a color-painting prototype robot to serve in relevant industries.

Experimental results obtained when applying the calibration procedure on a Hexa parallel robot show that vision-based kinematic calibration yields enhanced and efficient positioning accuracy.

The enhanced results show the advantages of this method in comparison with the previous calibration methods.

Contributing to the literature on movement structure in authoritarian regimes, this analysis focuses on the structure of two Iranian movements. We use a multi-method approach to analyze the organization of the student and women’s movements in Iran between 1997 and 2008. From 1997 to 2004, a reform government opened political opportunities. The period between 2005 and 2008 was characterized by increased repression. The student movement was organized during the first period as a hybrid composed of several networks linked in a federal structure. As the political context changed, the movement became less centralized. Its strategy shifted from one based in alliance with governing reformers to coalition building outside of the regime. In contrast, the women’s movement was organized as a densely linked web of noncentralized campaigns. The women’s movement overcame divisions as political opportunities closed in the mid-2000s and built a grassroots strategy during the latter part of the decade.

The purpose of this paper is to propose an approach for managing relevant factors and activities for implementing data governance in an organization. The process of assessing the establishment of data governance in an organization is intrinsically imprecise, due to the characteristics of new problem settings, particularly in relation to newly generated alternatives or vaguely defined qualitative assessment criteria.

To reject the inherent subjectiveness and imprecision involved in the evaluation process, the authors use the concept of fuzzy logic in this approach for developing the assessment model and analyzing the model for allocating the management efforts in the most efficient way to improve the data governance deployment level.

This paper identifies relevant factors and activities for implementing data governance in an organization and evaluates the state of data governance based on causal relationships between influential factors. In this study, factors are prioritized for effective allocation of limited management efforts in any improvement plan.

The interrelationships among factors are contextual and based on the perceptions of experts who may be biased as per their background and area of expertise. Meanwhile, lack of a data governance plan may cause failure during its implementation in an organization, as the worth of an organization's data will not be determined precisely. The paper has tremendous practical implications for organizations that intend to implement the data governance program and evaluate its state to design an improvement plan.

The paper proposes an approach for implementing data governance in an organization faced with limited resources for improvement.

This study utilized “social cognitive theory” to compare the impacts of organizational members' hedonic and work-related use of public social networks (SNs) and enterprise social networks (ESNs) on job satisfaction.

The participants comprised 240 employees who were able to simultaneously use SNs and ESNs in the workplace with regard to both hedonic and work-related motives. The measurement and structural models were evaluated using partial least squares structural equations modeling (PLS-SEM).

The results show that organizational members' hedonic and work-related use of public SNs enhances job satisfaction. However, the hedonic and work-related use of ESNs has negative and positive impacts on job satisfaction respectively.

The main theoretical contribution of this study lies in showing that employees' use of social networks does not necessarily entail detrimental or beneficial consequences and depending on different factors the outcomes are different. Following a comprehensive review of the literature, users' incentives and platforms emerged as two different factors contributing to the outcomes arising from the use of social networks in the workplace. Although a few studies have explored the impacts of organizational members' use of social networks on job satisfaction, none have done so in relation to different user incentives and platforms.

This study aims to address the relationship between economic complexities (EC) and the green economy (GE) with fraud in the listed companies on the Tehran stock exchange. The authors study whether EC and GE increase the detection of financial statement fraud.

The authors used a multiple regression model based on the panel data method and fixed effect model to test hypotheses. The sample includes 1,351 companies listed on the Iranian stock exchange from 2014 to 2021.

The results show a negative and significant relationship between EC and GE with financial statement fraud.

Since this research is the first to address the mentioned topic in emerging markets, it provides helpful insights for financial statement users, analysts and legal entities. The study fills the literature gap and promotes knowledge regarding its relevant literature.

This study aims to analyze the relationship between economic complexity (EC) and the green economy (GE) with the real and accrual earnings management (REM and AEM) of the listed companies on the Iranian stock exchange. The authors study whether EC and the GE can affect REM and AEM.

The authors used a multiple regression model based on the panel data and a fixed effect model to test hypotheses. The sample includes 1,351 companies listed on the Tehran Stock Exchange from 2014 to 2021.

The results show a positive and significant relationship between EC and the GE with REM and AEM.

Considering the importance of a GE and since this research is the first to address the mentioned topic in emerging markets, it provides helpful insights for financial statement users, analysts and legal entities. Our study fills the literature gap and promotes knowledge regarding its relevant literature. Examining this relationship portrays the latest research perspectives in this field. The information from this study can assist in environmental management decision-making and relevant policymaking, promoting the movement toward sustainable development.

This study aims to examine the underlying mechanisms through which entrepreneurial marketing (EM) promotes the development of a favorable brand image and enhances sales growth and market share in new ventures (NVs).

The authors tested the theoretical model using a multi-informant design in which survey data were collected from NV entrepreneurs and marketing managers. Hypotheses were tested using linear regression and PROCESS analysis.

The authors demonstrate the significance of EM as comprising two NV capabilities – first, the level of complementarity between entrepreneurial orientation (EO) and market orientation (MO) as a dynamic capability, and second, brand management capabilities (BMCs) as an operational capability – in shaping a favorable NV brand image and promoting market performance.

The authors offer a novel perspective by demonstrating that EO and MO yield complementarities in driving NVs’ BMCs, which, in turn, drive brand image development and market performance for NVs. In doing so, the authors demonstrate novel theoretical implications for the relevance of EM to NV branding, which, to date, has received scant attention in the literature.

The authors identify a potential avenue for entrepreneurs and NV managers to mitigate the potential failure rates by simultaneously pursuing a higher level of EO and MO and investing in brand-building activities. Such efforts can help enhance brand image, drive sales growth and foster long-term success.

To the best of the authors’ knowledge, this study is the first to include brand capabilities as an element of EM, examine EM in NV brand image development and identify the role of EM capabilities relevant to NV brand building and market performance simultaneously.

The purpose of this paper is to evaluate the relationship between the characteristics of the audit committee and the board and profitability among the companies listed on the Tehran Stock Exchange (TSE) in Iran.

In this study, the companies listed on the TSE during the period from 2010 to 2015 are investigated. The Linear panel regression method is employed for this purpose. The independent variables of the study are composed of some corporate governance mechanisms including audit committee size, audit committee expertise, board size, board independence, chief executive officer (CEO) duality, and institutional ownership.

In spite of the fact that there does not exist any significant association between audit committee size and corporate financial performance, the results indicate that there is a positive and significant relationship between audit committee financial expertise and profitability. The authors found that the number of board members cannot affect corporate performance; moreover, duality of CEO role in Iranian companies does not affect company performance. However, the outcomes showed a positive and significant association between the proportion of outside directors on the board (board independence) and profitability at 99 percent confidence level. This implies that the role of non-executive directors in Iran is inconsistent with the stewardship theory. This is due to the fact that independent directors understand the status of business and market better than the board’s executive members. Finally, the results indicated that there is no significant association between institutional owners and Iranian companies’ performance.

The findings of this study will reveal more than ever the role of corporate governance mechanisms for society and users of financial statements because as tools on the CEO actions, they always have to pay attention to the implementation of corporate principles in the economic entity’ operation.

This is one of the most important studies that simultaneously examine the impacts of characteristics of the audit committee and the board on profitability in an emerging market, and the results of the study may give strength to Iranian as well other developing countries.

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.

The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

The proposed methodology can be applied to find the best logistic plan in real situations.

In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.