This study informs the academic and policy debate on the policy effectiveness of exchange rate interventions on exchange rate levels and volatility. Using a constructed data set comprising daily data on exchange rates, monetary policy fundamentals, exchange rate intervention dates and magnitudes of those interventions as well as financial news speculation of such interventions, we empirically estimate the policy effectiveness of Bank of Japan interventions in the exchange rate over the 12-year period between 2010 and 2022. This allows us to investigate the policy effectiveness of a variety of exchange rate interventions, or news of exchange rate interventions, across different time-horizons. We find that policy interventions in the yen exchange rate are more effective over short-horizons than long-horizons, more effective when the policy objective is a competitive devaluation of the yen rather than a revaluation, and more effective at influencing the level of the yen against major world currencies other than the US dollar. In fact, for the yen-dollar rate, we find that policy interventions may have the unintended consequences of weakening the yen (when the policy intention is to strengthen it) and increasing volatility in the yen-dollar exchange rate.
The banking sector is a pillar of the world’s economic fabric and is today facing a major revolution due to the demands of sustainable development objectives and the evolution of sustainable finance tools. This article analyses the impact of green credit on commercial banks’ performance based on data from 10 commercial banks in China between 2012 and 2022. The study found that in the short term, the implementation of green credit has a positive effect on the income level of commercial banks’ intermediate activities and a moderating effect on their return on total assets and non-performing loan ratio.
Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.
In the current competitive global marketplace, innovation is key for high-tech firms to thrive. Open innovation offers a promising approach, but its effectiveness remains unclear. Therefore, this research explored the connection between open innovation, knowledge management capability, and innovation performance within high-tech firms. We used a mediation approach to highlight the central role of knowledge management capability in the relationship between open innovation and innovation performance. We used a survey questionnaire approach to collect data from the 462 employees of high-tech firms on open innovation, knowledge management capability, and innovation performance using a convenient sampling technique. We used partial least square structural equations modeling through PLS-SEM statistics. Results indicated that open innovation has a direct, positive and significant connection with innovation performance. Similarly, the current research serves as a pioneering exploration into mediation analysis, highlighting the mediating role of knowledge management capability that influences the relationship between open innovation and innovation performance. Empirical studies offer valuable insights for leaders of high-tech firms, guiding them to identify effective knowledge management practices and determine the ideal extent of open innovation to boost innovation performance. The current study reveals novel insights into the benefits of knowledge management capability in enhancing open innovation efforts within firms. This research provides valuable implications and future research directions.
Problem statement: An environmentally conscious consumer’s perspective can shift as they look for things that are gentler on the planet. Conversely, businesses engage in greenwashing when they try to cover up their lacklustre environmental initiatives. The current research was used the theory of rational choice behaviour to examine a model that connects corporate green washing and consumers’ green purchase intentions via the mediating roles of perceived risk, green trust and green confusion about food and beverage brands in Saudi Arabia. Research motivation: Sustainable business practices have been developed and adopted by corporations in response to the growing interest in environmentally friendly lifestyles and green products. However, green washing has become increasingly common as a means for businesses to give off the impression that they care about the environment when they really don’t. Research methodology: The online survey was used to obtain data directly from consumers about their views on green washing by corporations. Primary data was analysed using appropriate statistical tools and techniques in SPSS, AMOS and SmartPLS software, such as Correlation, Regression, Structural Equation Modelling (SEM), etc. Results: In terms of perceived greenness and confusion, the results showed that green wash mediates the relationship between green purchasing intention and greenness. There is a two-way correlation between consumers’ intentions to buy environmentally friendly products and their levels of green perception, and green confusion. The findings of this study were broadening our understanding of the consequences of green washing. Conclusions: All things considered, the study was encouraging more research on the subject and be a useful tool for academics, corporate managers, and students interested in environmental sustainability, product innovation, and green branding. According to the results, businesses can improve their green purchasing intentions by cutting down on green washing and focusing instead on building a positive reputation for their brand and encouraging customer loyalty. Corporate performance and social environment sustainability can both benefit greatly from this paper’s expansion of knowledge regarding the processes of individual customer psychological effects after perceptions of corporate greenwashing behaviour.
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