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Auditors should realize misstatements and communicate to managers for adjustments. Managers usually modify the misstatements, but they have motivations, like earnings management, for not altering the misstatements. The auditor expects to identify the misstatements’ earnings management, inform the managers and reduce earnings management by proposing adjustments. This study aims to determine whether identified and adjusted misstatements cause a decline in earnings management. Is the increase in the materiality of identified and adjusted misstatements associated with a reduction in earnings management?

The identified and adjusted misstatements are obtained from the difference between nonaudited financial statements and audited ones. Earnings management is computed using the adjusted Jones model, and the quantitative materiality threshold has also been calculated based on the Iranian auditors’ guidelines. These variables and other required information were gathered for 159 listed firms on the Tehran Stock Exchange during 2014–2019 and examined by the regression models.

The results show a negative relationship between identified and modified misstatements of total assets and earnings management and a positive and significant relationship between identified and adjusted misstatements of total liabilities and earnings management. However, the positive relationship between identified and adjusted misstatements of net income with earnings management is not significant. Besides, the relationship between the materiality difference and an absolute value of identified and adjusted misstatements (materiality minus the absolute value of misstatements) of total assets and earnings management is positive and significant, but the negative association between materiality difference and the absolute value of identified and adjusted misstatements of total assets and earnings management is not significant. The relationship between materiality difference and the absolute value of identified and adjusted net income and earnings management misstatements is negative and significant. These results indicate that the more material the identified and adjusted misstatements, the less earnings management.

The difference between nonaudited and audited financial statements represents identified and adjusted misstatements (audit adjustments). The client probably made some adjustments, but separating these adjustments from the auditor’s identified items was impossible with the available data.

The results show that significant audit adjustments decline earnings management. Paying more attention to a high-quality audit performed by the audit firms, auditors, managers and users and, consequently, discovering misstatements and adjusting or reporting them would decline the earnings management’s unfavorable impacts.

The unfavorable consequences of earnings management can cause the inappropriate transfer of wealth in the capital market and some investors’ loss to others’ benefit. These consequences can cause a loss of trust and leave unfavorable psychological effects on the capital market and society. Identifying and adjusting significant misstatements can lead to the decline of such impacts.

The previous studies assessed the relationship between identified and adjusted misstatements (audit adjustments) and earnings quality or earnings management. However, this study focuses on audit adjustments’ materiality to assess the impact of significant adjustments on earnings management.

Plant materials continue to play a major role in primary health care as therapeutic remedies in many developing countries. Medicinal herbs contain physiologically active principles that over the years have been exploited in traditional medicine for the treatment of various ailments as they contain antimicrobial properties. This paper aims to determine the antibacterial activity of Iranian endemic plants.

Antibacterial activities of ethanol extract and essential oil of ten Iranian folklore herbs including Heracleum lasiopetalum Boiss., Hypericum scabrum L., Thymus daenensis Celak., Ziziphora teniur L., Echiophora platyloba L., Dracocephalum multicaule Benth., Kelussia odoratissima Mozff., Mentha longifolia Hudson., Achillea kellalensis Boiss. and Arnebia euchroma (Royle.) Johnston. were investigated against Yersinia enterocolitica PTCC 1151 by agar disc diffusion and serial dilution assays.

Most of the extracts and essential oils showed some antibacterial activity against the tested bacteria with the diameter of inhibition zone ranging between 9 and 16 mm. Of the plants studied, the most active extracts were those obtained from essential oil of H. lasiopetalum fruits and ethanol extract of A. euchroma roots. The MIC values for active extract and essential oil ranged between 0.039 and 0.156 mg/ml.

The results obtained appeared to confirm the antibacterial potential of the plants investigated.

The essential oil <0.039 mg/ml of H. lasiopetalum fruits could be used as natural antibacterial agent Y. enterocolitica in the food preservation and human health.

This paper aims to investigate the corrosion behavior of AZ31 alloy as a prospective biomedical implant in two different simulated biological solutions and various immersion times.

Results of electrochemical experiments indicated that corrosion resistance of specimens immersed for 24 h was superior, suggesting that the surface layer is capable of protecting alloy.

Scanning electron micrographs revealed that this layer abounds with cracks, exhibiting optimum quality in 24 h immersion time, after which it begins to develop corrosion pits. Energy dispersive spectroscopy analysis suggested that the layer is mainly composed of magnesium hydroxide with precipitates of P and Ca containing species present on its surface, which is an indication of biocompatibility.

Finally, corrosion performance of Mg alloy was found to be slightly better in Lac-simulated biological solution (SBF) solution, which is more representative of actual physiological environment as compared to conventional SBF solutions.

A couple of decades ago, the negotiated syllabus was introduced as an alternative to the predetermined syllabus. The review of the related studies shows the number of studies on the use of negotiated syllabus in English language teaching is scanty. The main purpose of the study was to explore the advantages/merits of employing negotiated syllabus in general English courses that undergraduate students take.

The authors employed the phenomenology research method to deeply delve into the undergraduate students' perceptions of the advantages of the negotiated syllabus. The phenomenology method is used for investigating human lived experiences through the descriptions given by the people involved in the study. This qualitative research method is mainly used to study fields with little or no knowledge. The authors collected the data through in-depth interviews with the informants (18 students) who were selected through theoretical sampling. The informants were undergraduate students at Allameh Tabataba'i University who were selected through theoretical sampling. The authors listened to the recordings to transcribe the participants' statements and remarks verbatim. Then, we analyzed the interviews thematically through open, axial and selective coding. This study aimed at exploring the participants' perspectives on the advantages of the negotiated Syllabus. The study's main objective was to investigate the advantages/merits of employing negotiated Syllabus in undergraduate students' general English courses.

Findings revealed that employing the negotiated syllabus resulted in many advantages which were reduced into three axial coding: psychological, pedagogical and individual. Generally, the negotiated syllabus reduces the students' anxiety, improves their motivation, affects their language achievement and develops their critical thinking and learner autonomy.

Teachers are recommended to minimize the constraints and use the negotiated syllabus to optimize language learners' motivation and language achievement in teaching English programs.

The impact of the negotiated syllabus on language learners has been investigated through quantitative research methods. However, the language learners' perceptions of the negotiated syllabus have not been well explored qualitatively.

The purpose of this study is to investigate the moderating role of honesty-humility of financial managers on aggressive financial reporting behavior.

To test the research hypotheses, a scenario-based questionnaire taken from Brink et al. (2018) was used. Using a cross-sectional survey design, the authors collected primary data of 160 financial managers of firms in Iran using structured questionnaires. The research sample selected was based on Cohen et al.’s (2000) table. To test the research hypotheses, analysis of variance was used.

The results showed that increasing honesty-humility of financial managers decreases the impact of social pressure and risk appetite interaction on aggressive financial reporting. In addition, the results of further analysis showed that reducing the honesty-humility of financial managers increases the impact of risk appetite on aggressive financial reporting. Moreover, the results indicate that reducing the honesty-humility of financial managers increases the impact of social pressure on aggressive financial reporting.

This finding provides significant evidence for auditor, managers and policymakers in Iran. Policymakers, auditor and company managers can emphasize compliance with the code of ethics, internal control and corporate governance to increase ethics and reduce negative economic consequences.

To the best of the authors’ knowledge, this is the first case in an emerging economy to survey the moderating role of honesty-humility of financial managers on aggressive financial reporting behavior. Also, this study contributes to understanding how factors at the individual, social and organizational level combine to influence financial managers’ aggressive financial reporting behavior.

The purpose of this paper is to analyze demand forecast strategies to support a more sustainable management in a pallet supply chain, and thus avoid environmental impacts, such as reducing the consumption of forest resources.

Since the producer presents several uncertainties regarding its demand logs, a methodology that embed zero-inflated intelligence is proposed combining fuzzy time series with clustering techniques, in order to deal with an excessive count of zeros.

A comparison with other models from literature is performed. As a result, the strategy that considered at the same time the excess of zeros and low demands provided the best performance, and thus it can be considered a promising approach, particularly for sustainable supply chains where resources consumption is significant and exist a huge variation in demand over time.

The findings of the study contribute to the knowledge of the managers and policymakers in achieving sustainable supply chain management. The results provide the important concepts regarding the sustainability of supply chain using fuzzy time series and clustering techniques.

Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks.

In this paper, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, the analytic hierarchy process (AHP) is used to rank the results. Then, a real example is resolved by two important techniques in decision-making process, that is the AHP and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), as well as data envelopment analysis (DEA). The results from the above three methods are compared.

The results of this paper show that by using fewer criteria, the results from AHP and TOPSIS are very similar. Also, the results from these techniques vary from DEA’s ones in many aspects. So regarding the different results and the importance of criteria in selecting the Six Sigma projects, multi-criteria decision-making (MCDM) techniques are more reliable in comparison with DEA, because decision-maker’s point of view is more effective in MCDM techniques.

The paper, using a real case study, provides important new tools to enhance decision quality in Six Sigma project selection.

The purpose of this paper is to develop a slack-based measure (SBM) model in the presence of dual-role factor. Then it is applied in supplier selection problem.

The developed model in this paper is based on data envelopment analysis (DEA) technique.

The proposed evaluation platform is capable of identifying ill-performing suppliers which seek to future improvement. The findings provide valuable insights for practitioners, as well as academicians, policy makers and also integrate selection criteria under the supply chain.

This is the first time that a non-radial DEA model considers dual-role factors. The proposed model does not deal with dual-role factor as a non-discretionary factor. The proposed model considers dual-role factors on both the input and output sides in a similar manner. The proposed model can fully measure the inefficiency of suppliers. The proposed model can give a complete ranking of suppliers.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

The purpose of this paper is to propose a data envelopment analysis (DEA) method for customers' evaluation.

This paper introduces a variable return to scale (VRS) cross‐efficiency (one of the DEA models) to evaluate customers. This new model can consider ratio values and give a complete ranking of customers.

It is found that the proposed model can evaluate customers in a multi criteria context; does not demand weights from the decision maker; and can consider both the ratio and absolute numbers. An aggressive form of the VRS model is formulated to evaluate the peer‐appraisal value of customers instead of self‐appraisal.

To the best of the authors' knowledge, there is no reference that uses cross‐efficiency model with the ratio values for customers' evaluation.