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The purpose of this paper is to compare the transformational leadership style of women business owners and those women in the top position of organizations with women executives who are not in the top leadership position of organizations.

A quantitative approach using a population and business owners and executives from the private sector of the American Management Association.

The findings support the relationship between a woman owning a business or being in the top position and the increased use of transformational leadership behaviors.

The paper analyzes data collected in 1997 and the changes to the demographics may in fact be a limitation of the study.

The study focuses on the importance of contextual considerations in the study of women and their use of transformational leadership.

The case is set in the Fall of 2008 as Susan Schor, Chief Culture Officer, at EILEEN FISHER Inc. is meeting with the other two members of the Facilitating Leader Team, Jim Gundell, Vice President of Retail and e-Commerce and Jonci Coukier, Vice President of Design and Merchandising Processes, as well as founder, Eileen Fisher. Faced with significant projected financial loss in 2009, Susan reflected on the evolution of the company as influenced by her perspective with her organizational behavior expertise and collaborative leadership that embraced a values-based culture. Stories, voices and structures are examined in this retrospective view as Dr Schor sets the stage for how this example of best practice leadership will tackle the challenge at hand.

The research for this case was conducted over an 18-month period with over 40 interviews, extensive observation of the various teams at EILEEN FISHER Inc., and review of corporate communications, publications and other secondary sources. This case focuses on stories and voices that explain the unique leadership of EILEEN FISHER. The use of extensive quotes allows for an authentic “hearing” of the experiences and values as well as allowing the students to better understand the nature of qualitative data. Some of the discussion questions are posed as experiential exercises as this method allows the students to better relate to understand and apply values concepts.

Graduate and undergraduate organizational behavior, leadership, retail management and ethics.

The paper aims to track the development of service dominant logic (SDL) applied to brand management and highlights its essential elements. The paper attempts to extend the application of SDL to a form that makes the consumer part of the development process, a solution dominant approach.

The paper reviews the literature and suggests how brand managers can use service concepts, based on service‐dominance logic, to develop their new and differentiated products. The key is the relationship that customers develop with products, not the providers of those products, and how technology contributes to these linkages. This view, termed solution dominant, extends service dominant thinking. The paper also elaborates on the events and developments that have moved product development more firmly in the direction of relationships. Finally, it re‐examines some of the techniques that product developers use from a relationship perspective.

The relationship is the most important element in brand management. Relationships can take many forms based on the partners. While brand managers have traditionally focused on the relationship of the consumer with the brand, other relationships exist and are important. The internet has made it possible for consumer‐to‐consumer relationships to flourish. That presents both a challenge and opportunity for brand managers. Finally, an impending technological change reveals the potential importance of another relationship, consumer to thing (like a software application) which can build a bond, a relationship, between the consumer and a brand. The last logical possibility, thing‐to‐thing relationships already exist and their importance to brand managers is covered.

Service dominant logic and a focus on relationships has already been applied to brand management with success. It helps to refine the practice of branding. Consideration of a solution dominant logic, may help refine the practice further.

While service dominant logic has been applied to brand management, solution dominant logic, in which the consumer is part of the product/service design process has not been.

The purpose of this paper is to examine whether there exist significant benefits from diversification into frontier markets for an Australian investor in comparison to a US investor.

The study uses the computationally efficient ADCC GARCH model to estimate time-varying correlations of returns. The authors also compare the results to DCC GARCH correlations in order to test whether the results are model-specific. Optimal portfolios with several restrictions were constructed and the results from Australian and US investors were compared. The study also uses a holding out period that is rebalanced at the end of each quarter using new portfolio weights.

The study finds that there are significant benefits for the Australian investor from diversifying into frontier markets. However, the benefits to the US investor are much higher than that of an Australian investor. The results from the holding out period also present significantly higher benefits to the US investor compared to the Australian investor.

This study examines the diversification benefits to the Australian investor from frontier markets and compares the benefits of the Australian and the US investors. The results emphasise the potential benefits from including frontier markets in the portfolio. The paper also presents a holding out period analysis.

The investigation of the fractal nature of financial data has been growing in the literature. The purpose is to investigate the multifractal behavior of frontier markets using multifractal detrended fluctuation analysis (MFDFA).

This study used daily closing prices of nine frontier stock markets up to 31-Aug-2020. A preliminary analysis reveals that these markets exhibit fat tails and clustering patterns. For a more robust analysis, a combination of Seasonal and Trend Decomposition using Loess (STL) and MFDFA has been employed. The former method is used to decompose daily stock returns, where later detected the long rang dependence in the series.

The results confirm varying degree of multifractality in frontier stock markets, implying that they exhibit long-range dependence. Based on these multifractality levels, Serbian and Romanian stock markets are the ones exhibiting least long-range dependence, while Slovenian and Mauritius stock markets indicating highest dependence in their series. Furthermore, the markets of Kenya, Morocco, Romania and Serbia exhibit mean reversion (anti-persistent) behavior while the remaining frontier markets show persistent behaviors.

The information given by the detection of the fractal measure of data can support for investment and policymaking decisions.

Frontier markets are of great potential from the perspective of international diversification. However, most of the research focused on other emerging and developed markets, especially in the context of multifractal analysis. This study combines the STL method and a physics-based robust technique, MFDFA to detect the multifractal behavior of frontier stock markets.

The purpose of this paper is to examine herding in four frontier markets in the Balkan region, namely, Bulgaria, Croatia, Romania and Slovenia, from October 2000 to December 2016.

The author employs Chang et al.’s (2000) cross-sectional dispersion approach to capture herding, while also testing for the global financial crisis’ effects and the European Union (EU)/Euro zone accession effects over herding. Potential asymmetric herding effects conditional on market performance, domestic volatility, German and US investor sentiment are also examined. Finally, the cross-market herding dynamics of the region are also explored.

Overall, Romania exhibits the most extensive evidence of herding across various estimations. The empirical results indicate that cross-market herding dynamics within the region generate stronger herding (compared to the herding observed within each stock market individually), suggesting that Balkan stock exchanges’ growing financial integration leads their herding to be “imported”, rather than domestically motivated.

The findings provide useful insights for regulators in frontier markets, considering the destabilising potential of herding; they are also of particular interest to the investment community for reasons of international asset allocation, diversification and hedging strategies.

This study contributes to the limited herding literature regarding frontier markets and provides novel findings regarding the herding dynamics in the Balkan region, the EU/Euro zone accession’s effect and global factors’ impact on herding estimations.

In this chapter, we investigate the effect of long memory in volatility on the accuracy of emerging stock markets risk estimation during the period of the recent global financial crisis. For this purpose, we use a short (GJR-GARCH) and long (FIAPARCH) memory volatility models to compute in-sample and out-of-sample one-day-ahead VaR. Using six emerging stock markets index, we show that taking into account the long memory property in volatility modelling generally provides a more accurate VaR estimation and prediction. Therefore, conservative risk managers may adopt long memory models using GARCH-type models to assess the emerging market risks, especially when incorporating crisis periods.

The purpose of this paper is to assess to what extent intraday data can explain and predict long-term memory.

This article analysed the presence of long-memory volatility in five Asian equity indices, namely, SENSEX, CNIA, NIKKEI225, KO11 and FTSTI, using five-min intraday return series from 05 January 2015 to 06 August 2015 using two approaches, i.e. conditional volatility and realized volatility, for forecasting long-term memory. It employs conditional-generalized autoregressive conditional heteroscedasticity (GARCH), i.e. autoregressive fractionally integrated moving average (ARFIMA)-FIGARCH model and ARFIMA-asymmetric power autoregressive conditional heteroscedasticity (APARCH) models, and unconditional volatility realized volatility using autoregressive integrated moving average (ARIMA) and ARFIMA in-sample forecasting models to estimate the persistence of the long-term memory.

Given the GARCH framework, the ARFIMA-APARCH long-memory model gave the better forecast results signifying the importance of accounting for asymmetric information when modelling volatility in a financial market. Using the unconditional realized volatility results from the Singapore and Indian markets, the ARIMA model outperforms the ARFIMA model in terms of forecast performance and provides reasonable forecasts.

The issue of long memory has important implications for the theory and practice of finance. It is well-known that accurate volatility forecasts are important in a variety of settings including option and other derivatives pricing, portfolio and risk management.

It could be said that using long-memory augmented models would give better results to investors so that they could analyse the market trends in returns and volatility in a more accurate manner and reach at an informed decision. This is useful to minimize the risks.

This research enhances the literature by estimating the influence of intraday variables on daily volatility. This is one of very few studies that uses conditional GARCH framework models and unconditional realized volatility estimates for forecasting long-term memory. The authors find that the methods complement each other.

The purpose of this paper is to examine volatility and the weak-form efficient market hypothesis (random walk) of world spot crude oil market.

The study uses the generalized autoregressive conditional heteroskedasticity (GARCH-M), exponential generalized autoregressive conditional heteroskedasticity (EGARCH), and threshold GARCH (TGARCH) models. The data are selected from three markets: Dubai Vetch (DV), West Texas Intermediate, and Europe Brent Spot Price.

The weak-form efficient market (random walk) hypothesis was rejected for all estimated GARCH-M, EGARCH, and TGARCH models, indicating that these markets are inefficient and predictable. For daily data, the empirical results showed the presence of asymmetric effects, and the conditional variance process was found to be highly persistent.

This study is unique in its nature as it examines three markets on three continents. In addition, one of these markets (DV) was not carried out by the previous study. This work takes into account the market location.