Paradox strategic cognition and ECSR in China: a three-tripod perspective

Literature rooted in institutional theory and stakeholder theory offers conflicting views on the relationship between environmental corporate social responsibility (ECSR) and financial performance. However, both failed to explain why firms interpret this relationship variously which is subjective to a firm’s strategic cognition. How firms interpret this relationship affects the ECSR decision and implementation. Drawing on the paradox theory, four hypotheses were proposed and examined using data from 170 manufacturing firms in China. This study found paradox strategic cognition positively affects ECSR. Legal enforcement inefficiency, competitive intensity and industrial power weaken the effect of paradox strategic cognition on ECSR.     

Development of Corporate Governance Regulations: The Case of an Emerging Economy

This paper investigates the development of corporate governance regulations in emerging economies, using the case of Bangladesh. In particular, the paper considers three issues: What type of corporate governance model may be suitable for an emerging economy such as Bangladesh? What type of model has Bangladesh adopted in reality? and What has prompted such adoption? By analysing the corporate environment and corporate governance regulations, the paper finds that, like many other developing nations, Bangladesh has also adopted the Anglo-American shareholder model of corporate governance. Analysis of behaviours of principal actors in the Bangladeshi corporate governance scenario, using new institutionalism as a theoretical foundation, then reveals that such adoption may be prompted by exposure to legitimacy threats rather than efficiency reasons.     

Financial openness and capital mobility: a dynamic panel analysis

Does unrestricted control on the movement of capital increase capital mobility? Theoretically, the answer is yes. This paper uses the Feldstein–Horioka savings–investment methodology to examine the impact of financial openness on the degree of capital mobility in 104 countries. Our estimates suggest that financial openness has increased capital mobility in developing countries, while its effect is statistically insignificant in OECD countries. This also implies that a developing country with more financial openness can have more access to external capital markets for borrowings. Foreign aid also appears to supplement domestic savings for investment in developing countries. In line with the previous findings, our study also confirms that capital is more mobile for developing countries.     

Culture and business networks: International business negotiations with Arab managers

The Arab world is an important economic region due to its natural resources, geographic location and political influence. However, limited attention has been paid to researching and understanding the way business is conducted in this region. We address this gap by exploring the key socio-economic, cultural and political factors that influence the negotiation process between Arab and non-Arab managers. Semi-structured interviews were conducted with 30 Arab managers in Lebanon with experience in international business. The findings of the study show that: Arab negotiators place emphasis on building relationships and use referent power (wasta); the political uncertainty influences the bargaining power of the Arab negotiators and political volatility in the country influences the Arab managers’ use of time during negotiations.     

Institutional affiliation of contributors to the American Economic Review, 1981–1990

In this article the author examines the institutional origin of authors in theAmerican Economic Review between 1981–90. Institutions are categorized into four broad groups, and rankings of institutions based on the number of pages/articles in theAER are developed. A high correlation is noted between the rankings in this paper and previous similar attempts. The main contribution of this study lies in its updating of earlier work.     

Long-Term Synthetic Puts

We present the possibility of replicating the performance of a long-term put, which is not available in the financial markets, by a set of other traded financial assets. First, a benchmark portfolio is formed out of one share of stock and one put on the stock with a certain exercise price and a long time until maturity. The general form of a portfolio, consisting of shares of stock, bonds, and options on the stock, is discussed, which is expected to perform like the benchmark portfolio. Then a class of these synthetic puts is examined to determine which type of synthetic put may dominate the others.     

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

Due to mounting environmental and social challenges, supplier selection has become one of the most critical tasks of project-oriented organizations. Because supplier selection can affect the long-term success and profitability of the organizations and their projects, directly, embracing sustainability can add value in the equation. Considering sustainability measures can positively guide project managers in making better decisions for the projects in the long term. Therefore, the current study attempts to provide a conceptual model for selecting the best supplier based on a sustainability framework in megaprojects. Meanwhile, decision-making methods can be employed as a proper tool to find the best supplier. Ordinal priority approach (OPA) is a recent development in multiple criteria decision making (MCDM), while it has many benefits compared with other methods like analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). However, this method cannot consider multiple ranks during the decision-making process, and using an uncertainty approach feels strongly. Grey systems theory (GST) can consider uncertainties with no need for large sample or proposing membership function. Hence, the current study employed the GST to consider multiple ranks for criteria and alternatives in the OPA method. This is the first time that a sustainable supplier selection framework has been presented for megaprojects with the aid of the Grey OPA (OPA-G) method. Finally, a case study has been examined to evaluate the performance of the proposed approach. The results show that the proposed approach can be used in real-world situations and it has acceptable performance under uncertainty conditions.     

Multiday expected shortfall under generalized t distributions: evidence from global stock market

Review of Quantitative Finance and Accounting - Earnings management research often uses discretionary accruals from Jones-type models. These models assume a linear relation between sales changes...     

Dynamic spillover effects among tourism,economic growth and macro-finance risk factors

Portuguese Economic Journal - This paper examines spillover effects among international tourism growth, economic growth and a group of major macroeconomic and financial variables in the US. The...     

Evaluating interpretable machine learning predictions for cryptocurrencies

This study explores various machine learning and deep learning applications on financial data modelling, analysis and prediction processes. The main focus is to test the prediction accuracy of cryptocurrency hourly returns and to explore, analyse and showcase the various interpretability features of the ML models. The study considers the six most dominant cryptocurrencies in the market: Bitcoin, Ethereum, Binance Coin, Cardano, Ripple and Litecoin. The experimental settings explore the formation of the corresponding datasets from technical, fundamental and statistical analysis. The paper compares various existing and enhanced algorithms and explains their results, features and limitations. The algorithms include decision trees, random forests and ensemble methods, SVM, neural networks, single and multiple features N-BEATS, ARIMA and Google AutoML. From experimental results, we see that predicting cryptocurrency returns is possible. However, prediction algorithms may not generalise for different assets and markets over long periods. There is no clear winner that satisfies all requirements, and the main choice of algorithm will be tied to the user needs and provided resources.