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The purpose of this article is to describe and analyze the occupational life cycle of Swedish real estate brokers.

Voluntary turnover among real estate brokers could lead to occupational turnover and/or employee turnover and has been described as problematic by both practitioners and researchers alike. Most previous studies focusing on this issue have explored connections between real estate brokers' personality, economic and market conditions and turnover. Employee turnover involves shifting jobs within the profession (real estate brokerage), whereas occupational turnover concerns movement to a job not related to the real estate brokerage profession. Both perspectives on turnover are however lacking data about the average time spent as a broker. This study fills this gap by exploring real estate brokers' life cycle through data analysis using a cohort study consisting of a sample of 5,304 real estate brokers registered and/or deregistered over a ten-year period from 2010 to 2019.

The analysis show that the decline is almost linear, resulting in 50% of the newly registered real estate brokers remain in the occupation eight years after registration. These findings are not in line with previous assumptions as the real estate brokers' life cycle is substantially longer. The results also reveal that there are differences in life cycles due to gender and year of registration.

The analysis of longitudinal, aggregated data on the life cycle of real estate brokers is highly relevant as it serves as a point of reference for future longitudinal studies analyzing the motives for leaving the occupation.

This study aims to evaluate the short-term impact of brokerage analysts’ recommendations on abnormal returns using a sample selected from the S&P BSE 100 in the Indian context. The efficient market hypothesis, specifically, its semi-strong form, is tested for “Buy” stock recommendations published in the electronic version of Business Standard. The crucial issue is, are there any abnormal returns that can be earned following a recommendation? If so, how quickly do prices incorporate the information value of these recommendations? It tests the impact of analyst recommendations on average abnormal returns (AARs) and standardized abnormal returns (SRs) to determine their statistical significance.

Using a sample of stock recommendations published in the e-version of Business Standard, the event study methodology is used to determine whether AARs and SRs are significantly different from zero for the duration of the event window by using several significance tests.

The findings indicate a marginal opportunity for profit in the short term, restricted to the event day. However, the effect does not persist, i.e. the market is efficient in its semi-strong form implying that investors cannot consistently earn abnormal returns by following analysts’ recommendations. Post the event date, the market reaction to analyst recommendations becomes positive, however, insignificant until the ninth day after the recommendation providing support to the underreaction hypothesis given by Shliefer (2000) and post-recommendation price drift documented by Womack (1996). The study contributes by using different statistical tests to determine the significance of returns.

There are important implications for traders, investors and portfolio managers. The speed with which market prices incorporate publicly available information is useful in formulating trading strategies. However, stock characteristics such as market capitalization, volatility and level of analyst coverage need to be incorporated while making investment decisions.

The study contributes by using different statistical tests to determine the significance of returns.

The purpose of this study is to investigate efficiency and productivity of Turkey’s both brokerage sector and intermediary institutions (IIs) that have been active in Turkish capital markets.

Data envelopment analysis (DEA) and Malmquist total factor productivity index (MPI) are used to analyze efficiency and productivity of Turkey’s both brokerage sector and 51 Turkish IIs constantly operated between the years 2008 and 2018. Paid-in capital, administrative expenses and trading volumes are used as input, while net trading commissions and net profit/loss are used as output in analysis. The calculations of this analysis are made with DEAP 2.2 program and Python.

The results reveal that during the analysis period, percentage of efficient institutions among 51 IIs was between 18% and 39% while the sector’s mean efficiency score ranged between 52% and 65%. While 2009 is the year with the highest number of efficient institutions, 2013 is observed to be the least. Finally, the results of productivity analysis indicate that all types of IIs are not fully productive during the related period. The striking finding obtained is that though there is a decrease in total productivity change, the technological change has a positive effect on their productivity change.

This study is a double-layered research paper that includes efficiency analysis by DEA in the first step and productivity analysis by using MPI in the second step.

This study aims to empirically examine the impact of the price structure of two-sided markets on transaction volume and market share (MS) in the context of the Korean credit card industry. The Korean credit card market differs from those in the United States (U.S.) or Europe in terms of transaction structure (i.e. a three-party system in Korea vs a four-party system in the U.S. or Europe) and government policy. In addition to the merchant discount rate and the cardholder annual membership fee rate, the authors included and analyzed exogenous variables to eliminate any endogeneity. Based on the analysis results, the authors found that credit card usage performance (i.e. transaction volume) increases with an increase in the relative price ratio (merchant discount rate ÷ cardholder membership fee rate) paid by merchants and cardholders, provided that the total price (merchant discount rate + cardholder membership fee rate) paid by merchants and cardholders remains constant. Therefore, this study is the first to confirm that the Korean credit card market operated as the theoretical mechanism of a two-sided market during the analysis period. This effect can only be observed in specific cases such as the launch of the so-called “Chief Executive Officer(CEO)-designed card.” When a new CEO takes office in a credit card company and launches a “CEO-designed card,” there is a significant increase in not only card usage performance but MS as well owing to the price structure changes caused by expanding the benefits that customers derive from card use.

The purpose of this paper is twofold: First, it analyzes demand and supply-side factors that influence patient flows to and from Austria. Second, building on the empirical research and existing conceptualizations, the study offers a general extended framework to guide future comparative analysis.

The paper draws on multiple data sources including a literature review, secondary data, website analysis and semi-structured interviews with patients and health providers. Content analysis was carried out to identify common motives for seeking care abroad and providers' orientation towards medical travel.

Outbound medical travel is largely determined by factors of access, affordability and vicinity, while inbound medical travel is predominately driven by a lack of adequate medical infrastructure in source countries and quality, both in terms of medical and service quality. Providers distinguish themselves according to the extent they take part in medical travel.

The findings emerging from a single country case study approach cannot be generalized across settings and contexts, albeit contributing to a better understanding of current medical travel patterns in Europe.

Unlike most recent contributions, this study focuses both on inbound and outbound medical travel in Austria and investigates patient flows for distinctive treatments and drivers. While analysis of the supply-side of medical travel is often limited to tourism studies, this study provides a critical insight into developments in Europe from a health policy perspective, acknowledging that diverse medical travel patterns in Europe coexist.

The purpose of this paper is to illustrate a profitable and original index options trading strategy.

The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented.

The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading.

The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.

Sports tourism was strongly affected by the COVID-19 pandemic, but there is no consensus on what sports tourism should look like in the post-pandemic period. This study explores the future of sports tourism in light of the COVID-19 pandemic and provides an alternative paradigm model.

Data were collected by interviewing sports tourism experts. Data analysis was based on the continuous comparison method during three stages of open, axial and selective coding.

The findings point to the complexity of the future sports tourism industry. Post-COVID-19 sports tourism strongly depends on environmental forces and targeted support, with strategies focused on tourists’ safety and security, digitalization of the industry, and new employment opportunities.

This study contributes to the body of knowledge on sports tourism by providing answers to the current challenges, threats and opportunities associated with the pandemic. The proposed paradigm model could be a guideline for sports tourism practitioners and policymakers to accelerate recovery from COVID-19 in a sustainable and resilient manner.

How does the interaction between time and knowledge affect the evolution of organizations? Past research in organizational evolution has mostly investigated time and knowledge as two separate variables. In contrast, theoretical perspectives integrating these variables are still seemingly scant. The authors believe that filling this literature gap needs attention. Thus, this study aims to contribute by developing a conceptual framework.

This is a conceptual study. The framework is centred on the concept of “co-evolutionary time”, which the authors explain through a business example from the tourism industry. Supported by a narrative-based style, from a methodological point of view the framework is featured by the attempt to synthesize specific, extant literature into new theoretical development.

As its main theoretical contribution, the co-evolutionary time suggests how firms can adapt in a way that, from an evolutionary perspective, proves fitting both in terms of contents and methods, thus opening possibilities for new long-term social construction and reconstruction. As its main practical contribution, co-evolutionary time can constitute not only a temporary source of organizational success and competitive advantage but also an agent of enduring change and long-term business survival.

As its main novelty, the framework is developed through merging two literature streams. In particular, the authors first consider the literature about time, with a focus on its objective and subjective dimensions. The authors then consider the literature about organizational evolution, with a focus on the co-evolutionary nature of the firm/environment relationship.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.