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The purpose of this study set out to introduce an alternative framework for explaining the formation of the innovation ecosystem based on the systematic literature review (SLR) and ecosystemic approach.

This paper is an SLR of studies from the year 2008-2018 that investigating startups’ innovation. SLR approach being used exploration, interpretation and communication method, which composed of seven steps as follows exploring topics, searching, organizing, evaluating and expanding, integrating and communicating. The output of this process is 63 documents that applied to synthesize the formation framework.

The systematic review of literature has shown that researchers in recent years have considered some entities such as incubators, financials suppliers, accelerators, universities and companies in relation to the startup innovations, which are described in this paper as key actors. The study of the relationship between these actors in the documents led to the identification of interactional necessities, including structures, infrastructures and networks. Finally, the processes studied in the literature were classified into three types of mechanisms, namely, the genesis, growth and development of startups innovations.

The SLR approach is subject to limitations because some poor explanations amongst previous researchers may be repeated and reinforced. Also, in the protocol adopted in this paper, documents are limited in English.

The introduced frammework can be useful in identifying and understanding the requirements of startups and creating effective policies for their innovation development.

This paper reviews, summarizes and integrates the growing and scattered literature of the innovation ecosystem of the startups and delivers new facts for the future development of this field.

In this paper the authors address the questions whether global financial crises cause oil shocks worldwide, then whether such shocks affect trade flows of both oil importing and oil exporting countries of East-West Asia. The purpose of this paper is thus to explore such effects by specifying basically a dynamic export model using data of the Asian economies countries over the period 1980-2008.

An ARDL specification is applied to show the dynamic effects of main determinants, including financial crisis and the world oil price, on the export flows of each country in the sample. The data for financial crisis have been compiled by Hatzius et al. (2010).

The results, as a whole, imply that both financial crisis and oil price have a cross-effects on Asian trade flows in the short run, while this effects could not occur in the long run.

The goal is to estimate an econometric model of exports to examine how recent crises affect export flows in the selected Asian countries. Different from previous studies in the literature, this paper first explores the interaction between financial crisis and oil shocks and second uses an extended and dynamic export model, based on ARDL approach. The core of the study relies on the question whether a cross-relationship between oil price and financial crisis affects the export flows of the Asian countries: China, Japan, Iran, Malaysia, Saudi Arabia, South Korea and Turkey which are both oil importing and exporting.

This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs.

The objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible.

Empirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs.

The proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.

The purpose of the current study is to examine the effects of spiritual and emotional intelligences of managers in manufacturing industries on the ambiguous activities of tax avoidance and corporate disclosure quality.

Managers of 178 manufacturing companies have undergone a test regarding spiritual intelligence and emotional intelligence, of which 119 responded to the online questionnaire. Information on these two psychometric items was collected through King–Baron standard questionnaire, and quantitative data on tax avoidance, disclosure quality and performance were collected through the Rahavard Novin application, financial statements and Stock Exchange website. Obtained data were analyzed using factor analysis and structural equation modeling.

The results show that a relationship exists between the level of intellectual skills of managers (spiritual intelligence and emotional intelligence) and tax avoidance activities.

The current study is almost the first study in developing countries which focuses on the subject of the study.

This study aims to assess the influence of material internal control weaknesses (ICWs) on investment in intangible assets, capital structure and commercial risk of organizations. Also, it analyses the impact of investment in intangible assets on the presence of material ICWs. This paper expects that ICWs and investment in intangible assets are interactively incorporated.

The statistical population of this study includes listed firms on the Tehran Stock Exchange during 2012-2017, selected using the systematic elimination method. A total of 588 firms is selected as the final sample of the study. Four hypotheses are developed to meet the study’s objectives and data analysis is carried out using the panel data method in Stata Software.

Results show that material ICWs have a positive and significant impact on investment in intangible assets and financial leverage. Moreover, this study finds that investment in intangible assets deteriorates the ICWs’ degree. However, the findings show no significant relationship between ICWs and commercial risks of companies.

The current study fills the gap in the literature science; there is no evidence on the subject of the study.

The purpose of this paper is standardize and provide a multidimensional measure for assessing human resources competencies (HRCs) scale.

The data collected in this study were 2018 from the 234 people selected from 603 managers and experts in human resources of selected firms existing in the Yazd Industrial Town randomly. Based on the model of HRCs designed by Ulrich et al. (2008), a questionnaire was developed to assess HRCs. Internal consistency and split-half methods were used to obtain the reliability of the instrument. Content validity and construct validity of the instrument were also assessed through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

This paper elucidates a key scale for assessing HRCs including three dimensions: knowledge business, functional expertise and managing change. Also, results revealed that two items were then dropped from the questionnaire as they were unreliable, and a final 31 items were extracted to form the scale for assessing HRCs. The coefficients for Cronbach’s α and split-half were 0.963 and 0.947, respectively. In EFA, Kaiser-Meyer-Olkin test yielded optimal 0.962, and Bartlett’s test was statistically significant. Additionally, three factors with eigenvalues higher than 1 explained 63% of the total variance. Hence, CFA confirmed the results from EFA too. Moreover, the model proved to enjoy a good fit.

The scale is useful for both researchers and practitioners. Also, the scale provides researchers with a sought-after conceptualization of HRCs.

Consequently, considering that the validity and reliability indices of HRCs were estimated to be desirable, the authors believe that the developed questionnaire can be used as an appropriate scale for measuring HRCs in future research.

This paper aims to draw a roadmap for the presence of Iranian academic libraries in the cloud infrastructure.

This research attends an applied-development one that is a part of developmental research due to its conceptual expansion, foresight and roadmap for the presence of cloud-based academic libraries and finally, becoming cloud libraries. Because of providing a roadmap template, the presence of academic digital libraries in the cloud and becoming a cloud library is applied research. Because of providing a roadmap template, academic digital libraries’ presence in the cloud and becoming a cloud library is one of the applied research areas. The statistical population of this research includes all Iranian digital academic libraries. There were 64 digital libraries out of which 59 libraries participated in completing the questionnaire.

Preliminary results from used Delphi method’s first round which was considered by 59 experts were identified typically and descriptive after appropriate component classification and editing. After identifying these factors, each of the roadmap levels in the third stage and the degree of relevance approved by the experts were reviewed and the most critical and relevant factors were identified as key components of the roadmap for the presence of cloud-based academic libraries and becoming cloud libraries. At this stage, they were selected as 24 factors, including seven factors for the first layer, eight factors for the second layer and nine factors for the third layer.

By introducing a roadmap for the presence of academic digital libraries in the cloud context, they will promote more and better interaction between academic libraries to offer services to users anytime and anywhere.

Demolition is a high-risk operation in construction projects that may lead to serious accidents. Risk assessment is a fundamental step in managing demolition risk and preventing casualties and financial losses. The present study aims to provide a framework to identify, analyse and evaluate the risks in building demolition operations.

According to previous studies and the use of expert knowledge, 10 possible risks of the building demolition operation were identified. Subsequently, these risks were assessed using a combination of fuzzy logic with fault tree analysis (FTA), criteria importance through inter-criteria correlation (CRITIC) and technique for order preference by similarity to ideal solution (TOPSIS). Then, the risks were classified with the help of a risk decision matrix (RDM), and appropriate treatment strategies were presented according to the level of importance of each risk.

Considering the obtained magnitude for each risk and its rating, building collapse and noise pollution were identified as the most and least significant risks, respectively. The results of this study were in good agreement with the data provided by the Iranian Ministry of Cooperatives, Labour and Social Welfare, as well as obtained results of the previous studies on demolition.

This paper provides a novel framework for assessing the risks in building demolition operations. The findings of this study help demolition project managers to manage the risks in their projects properly.