Search results

This study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.

The study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.

Empirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.

Apart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.

The uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

本研究旨在探討與通貨膨脹有關的狀況的組成部分(通脹預期 、通脹不確定性及體現了的通脹), 宏觀經濟不確定性及經濟衰退狀況的可能性、在一段特定時間內對美國銀行業的表現指數有何種程度的影響。

研究採用塞爾納 (Zellner) (1962) 提出的看似無關迴歸模型 (SUR)，去探討通脹狀況的特定組成部分及其它不利的宏觀經濟狀況如何影響美國銀行業內的績效動態。

實證證據暗示在被研究的各個不利宏觀經濟狀況中，通脹預期及宏觀經濟不確定性，對美國銀行業內的主要業績指標的約束影響, 與其它被探討的狀況相比，往往會較重大。相對地、本研究結果顯示通脹預期及宏觀經濟不確定性，對美國銀行業資本回報率的約束影響、往往遠多於資產收益率。研究結果進一步顯示，在被探討的三個銀行業績指標中，就本研究所探討的各個不利的宏觀經濟狀況而言，淨息差是脆弱性最小的銀行業績指標。

除了上述各實證結果外，本研究結果預期會給銀行業內機構間作戰略規劃的決定時提供資料，譬如，各項研究結果或可在制定旨在減少與特定業績指標如資本回報率相聯繫的脆弱性的政策和經營策略時提供資料。這脆弱性的減少，是透過嚴謹地研究各個業績指標，如何對在本研究中被探討的個別不利宏觀經濟狀況作出反應而達致的。這程序或許最終會幫助建立一個以減少各個不利宏觀經濟狀況對主要業績指標的影響為目的的量身定制措施／程序。本研究的結果，或許亦可為更多旨在減弱眾所周知的宏觀經濟狀況對銀行業運營效率的影響的適應性政策提供平台。

與文獻中可見的相關研究比較，本研究的獨特性源於其實證分析，是涉及在同一個構架內處理宏觀經濟狀況相互有關的組成部分的三個變體 (通脹狀況的不同變體) 。

This paper aims to explore the effects of a surge in tourism short-term rentals (STR) on housing prices in municipalities within Portugal’s two largest Metropolitan Statistical Areas.

This study applies the difference-in-differences (DiD) methodology by using a feasible generalized least squares (FGLS) estimator in a seemingly unrelated regression (SUR) equation model.

The results show that the liberalization of STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. This transfer led to a leftward shift in the housing supply and a consequent increase in housing prices. These price increases are much higher than those found in previous studies on the same subject. The authors also found that municipalities with more STR had low housing elasticities, which indicates that adjustments to the transfer of real estate from housing to tourism were made by increasing house prices, and not by increasing supply quantities.

The study suggests that an unforeseen consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases due to inelastic housing supply.

This is the first time that the DiD methodology has been applied in real estate markets using FGLS in a SUR equation model and the authors show that it produces more precise estimates than the baseline OLS FE. The authors also find evidence of a supply shock provoked by STR.

This paper aims to explore various factors associated with radio frequency identification (RFID) adoption with quantitative meta-analysis. More specifically, this paper attempts to measure key variables of RFID adoption derived from Rogers’ innovation theory and further examines how state intervention influences the process of RFID adoption. First, this paper compares, relying on a meta-analysis, various mean effect sizes among technological, organizational and environmental factors (i.e. government-driven policies) that Rogers suggested in his innovation model.

In mean effect size analysis, this paper finds that the technological factor is the most powerful factor that affects the RFID adoption. The technological factor is statistically significant across all regions, including North America, Europe and Asia. The organizational factor is significant only in developing countries like Southeast Asian countries and East Asian countries. Environmental factors like government intervention for facilitating RFID adoption are strong enough only in Southeast Asia and Europe.

This paper finds that government’s supportive policy is more effective in Europe but not in America, while external pressure is still more effective in Southeast Asia. These results implicate that developmentalism or government-driven policy can be effective not only in developing countries but also in the case of developed countries. In addition, this paper conducts a seemingly unrelated regression (SUR) analysis based on Fisher’s standardized score.

In SUR analysis, this paper finds that the correlations between RFID adoption intention and three innovation factors vary across industrial areas. More specifically, the manufacturing area shows negative moderating effect on all three equations where correlations between Rogers’ innovation factors and RFID adoption intention are meta-dependent variables. Also, RFID adoption is accelerated when the size of the firm is large or the location of the firm is in Southeast Asia. This result implicates that the aspect of technology adoption can be changed by region and type of industry.

This study explores the reasons behind the popularity of majoring in Public Relations as opposed to Journalism or Digital Media among mass communications undergraduates in Oman. It attempts to gain insight into the factors influencing students’ decision-making process in selecting their major. It explores factors such as choice of major and sources of information that shape students’ knowledge and perception of the majors, using variables such as knowledge of job market, knowledge of curriculum, information sources and personal influences shaping major choice and selection. The study confirms that perception of the job market is a crucial factor in the selection of the majors. It also reveals that family plays a crucial role in influencing students’ decision-making process while choosing a major. The study concludes that strengthening the role of the academic advisor and educating students on course content and learning outcomes can increase the acceptance of less popular majors among communication undergraduates. The study is relevant in the context that the falling numbers of student enrolments in some areas of media studies could lead to a decline in teaching and research activities in those areas, in addition to a possible shortfall of specific skilled professionals in the national labour market pool.

This paper aims to anticipate the influence of new cinematographic and television operators on the attractiveness of tourist destinations.

The methodology developed is two-fold: first, long-haul observation of the sector, and second, a state of the literature on the topic.

These platforms reshape the distribution of audiovisual content and influence consumer behavior. Through the detailed knowledge of users (user data, recommendation algorithm), the platforms have important information at their disposal to build future tourism trends.

In the continuity of research in film tourism, the authors question the impact of platforms that are now emerging as significant operators in the distribution and creation of audiovisual content.

In the ever fast-changing modern world, through the use of digital banking services (DBS), the old concept of banking in a traditional way has been completely changed. It was made possible through the use of modern artificial intelligence embedded technologies. It was done to meet the ever-growing demands of customers through more user-friendly and time-saving uses of technologies. This paper aims to uncover and analyse the factors affecting the adoption of digital banking services by rural micro small and medium enterprises (MSMEs). MSME is one of the most active sectors in India. It plays an important role in the economic development of the country through exports and domestic supplies and by creating employment opportunities.

The study was conducted using a questionnaire survey. In total, 148 rural MSME owners were considered for the analysis in this study. Rural MSMEs in India are way behind in using digital banking services than their urban counterparts. The present study uses IBM SPSS and AMOS to shed light on the prevalent factors that influence the attitude to use digital banking services.

It is found out that convenience (which includes perceived usefulness and perceived ease of use), perceived self-efficacy, demonetization, performance expectancy and pandemic effect have a significant effect on the attitude to adopt DBS. The findings of the study will provide deeper insights for the banks as well as different government agencies to revamp their strategies in changing the financial landscape of the country through a “cashless economy”.

Demonetization, a boom in eCommerce in India, pandemic-related lockdowns or restrictions and the government’s push for the digital economy will aid the use of DBS at a faster pace. The outcome of the study will help both the government and the financial institutions to chalk out strategies to cater to the rural MSMEs in embracing DBS.

The use of digital services for banking in India is in a nascent stage, but the rate of adoption is increasing at a cyclonic speed. Affordable electronic devices, cheap internet and different medium of using DBS are fuelling the rapid increase; yet, limited research focuses on the differences in the rate of acceptance of digital banking services concerning rural MSMEs.

In this paper, we examine whether fund market reactions are affected by the characteristics of categorized features of fund. To investigate the goal of the paper, we consider macroeconomic factors as well as financial characters. We classify fund flow into four groups depending upon type of fund and fund characters to determine which category is better to increase fund flow for capital market after these financial occurrence. In this regard, our research suggests important evidence about the effect of financial factor on fund flow with a case of an detailed situation in Emerging market. In order to test the hypothesis, we use seemingly unrelated regression (SUR) model to choose significant factors among various types of fund market-related changes. Our sample consisted of fund flows from 2006 to 2016 collected by Korean Financial Association and Bank of Korea. The empirical results are summarized as follows : First, we find that capital market index, exchange rate affect fund flows with time-lagged value changes. Second, the stock index fund and banking sector fund sales show strong positive relations with the fund flow changes. Third, values of the fund flow are significantly related with fund sales by asset management’s affiliated financial institution. These results are consistent with the hypotheses that the increase and decrease in the fund flows due to capital market situation are more pronounced as the financial factors fit. Our results suggest that it is necessary to consider the fundamental characteristics of fund flow changes as well as the external economic environment to get a more efficient market performance and supervision.

This paper aims to provide information about the structure of collaborative work among Argentinian economics. The study provides specific applied research of social network analysis focus on this profession in this specific country.

The contribution opted for applying social network analysis tools to papers presented in a congress and published in its proceedings. The authors focus in detecting main actors, groups of co-authorship, professionals acting as bridges between groups and differences between genders.

The paper provides empirical insights about how co-authorship has evolved between Argentine economists. The authors find that structural properties of the network, main actors, both male and female, main universities or center that affiliates them, a gender gap that might be closing out.

The paper focuses on the network for the period 1964-2014 without a more detailed dynamic. It also does not explain main topics worked by the authors.

The work provides knowledge about how groups are created in Economics in Argentina, how cooperation has evolved and what has been the role of women in this development. It also shows how different departments and entities collaborate with diverse success in the creation of new knowledge in Economics in Argentina.

The paper works with data from a source of information non-previously studied and contributes in explaining a particular type of collaborative work in a profession in Argentina.