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Alycen McAuley is the Director of Corporate Sponsorships for Charles Schwab, a Fortune 500 financial services company. Here she talks with Jay Gladden about the sponsorship industry, Schwab's goals with sponsorship, sponsorship evaluation and the future of corporate sponsorship.

Contrasting two countries with different gender regimes and welfare states, Sweden and Tanzania, this paper aims to analyse how the institutional context affects the ways in which a neo-liberal reform agenda is translated into institutional changes and propose how such changes impact the preconditions for women’s entrepreneurship.

This study uses document analysis and previous studies to describe and analyse the institutions and the institutional changes. This paper uses Scandinavian institutional theory as the interpretative framework.

This study proposes that: in well-developed welfare states with a high level of gender equality, consequences of neo-liberal agenda for the preconditions for women entrepreneurs are more likely to be negative than positive. In less developed states with a low level of gender equality, the gendered consequences of neo-liberal reforms may be mixed and the preconditions for women’s entrepreneurship more positive than negative. How neo-liberalism impacts preconditions for women entrepreneurs depend on the institutional framework in terms of a trustworthy women-friendly state and level of gender equality.

The study calls for bringing the effects on the gender of the neo-liberal primacy of market solutions out of the black box. Studying how women entrepreneurs perceive these effects necessitates qualitative ethnographic data.

This paper demonstrates why any discussion of the impact of political or economic reforms on women’s entrepreneurship must take a country’s specific institutional context into account. Further, previous studies on neo-liberalism have rarely taken an interest in Africa.

The study uses the multivariate GARCH-BEKK model (which was first proposed by Baba et al. (1990) and then further developed by Engle and Kroner (1995)) to examine the return and volatility spillover between India and four leading Asian (namely, China, Japan, Singapore and Hong Kong) and two global (namely, the United Kingdom and the United States) equity markets.

The study employs a multivariate GARCH-BEKK model to quantify return correlation and volatility transmission across the pre- and post-2008 global financial crisis periods (apart from other conventional time series modelling like cointegration, Granger causality using vector error correction model (VECM)).

The results show a tendency of the Indian stock market index to move along with the US and Hong Kong market indices. The decrease in the value of the co-integration coefficient during the recession was explained by reduced investor confidence in developing countries. The result further shows a clear distinction in terms of volatility spillover between the Asian market vis-a-vis US and UK markets. Volatility transmission from India to Asian markets was found to be significantly higher as compared to the US and UK. So also, the study’s results show a puzzling result giving us comparable co-integration ranks for phase 2 (expansion) and phase 3 (slow-down) of the business cycle in most cases.

In Granger causality testing, the results were unable to ascertain the difference between phase 2 (expansion) and phase 3 (slowdown). However, the multivariate GARCH (MGARCH)-BEKK model showed a clear reduction in volatility transmission to NIFTY50 (is the flagship index on the National Stock Exchange of India Ltd. (NSE)) as India entered slow-down. This shows that the Indian economy does go through different business cycles, and the changes in parameters hence prove hypothesis 3 to be true with respect to volatility transmission to India from International markets.

The results show that for all countries, the volatility transmitted to India increases significantly going from phase 1 (recession) to phase 2 (expansion) and reduces again once the countries enter slow-down in phase 3 (slowdown). This shows that during expansion shocks and impulses in international markets affect the Indian markets significantly, supporting the increase in co-integration in phase 2 (expansion). During expansion, developing markets like India become profitable for investors, due to the high growth rate when compared to developed countries. This implies that a significant amount of capital enters Indian markets, which is susceptible to the volatility of international markets. The volatility transmission from India to the US and UK was insignificant in phase 1 (recession and recovery) and phase 3 (slow-down) showing a weak linkage between the markets during volatile time periods.

This methodological paper demonstrates how service firms can use digital technologies to quantify and predict customer evaluations of their interactions with the firm using unstructured, qualitative data. To harness the power of unstructured data and enhance the customer-firm relationship, the use of computerized text analysis is proposed.

Three empirical studies were conducted to exemplify the use of the computerized text analysis tool. A secondary data analysis of online customer reviews (n = 2,878) in a service industry was used. LIWC was used to conduct the text analysis, and thereafter SPSS was used to examine the predictive capability of the model for the evaluation of customer-firm interactions.

A lexical analysis of online customer reviews was able to predict evaluations of customer-firm interactions across the three empirical studies. The authenticity and emotional tone present in the reviews served as the best predictors of customer evaluations of their service interactions with the firm.

Computerized text analysis is an inexpensive digital tool which, to date, has been sparsely used to analyze customer-firm interactions based on customers' online reviews. From a methodological perspective, the use of this tool to gain insights from unstructured data provides the ability to gain an understanding of customers' real-time evaluations of their service interactions with a firm without collecting primary data.

This research contributes to the growing body of knowledge regarding the use of computerized lexical analysis to assess unstructured, online customer reviews to predict customers' evaluations of a service interaction. The results offer service firms an inexpensive and user-friendly methodology to assess real-time, readily available reviews, complementing traditional customer research. A tool has been used to transform unstructured data into a numerical format, quantifying customer evaluations of service interactions.

The authors investigate whether matchings in equity crowdfunding are more likely to happen if homophily exists between investors and investees. They focus on gender, age and geographical proximity as crucial dimensions of similarity among individuals and thus of homophily. Furthermore, they investigate whether the effect of homophily depends on the risk of opportunism, which investors allegedly attribute to proponents basing on their area of residence.

The authors analyze a hand-collected database of 13 equity crowdfunding campaigns launched by Italian innovative start-ups from January 2013 to June 2016, which includes information about 384 equity crowdfunding investments carried out by 361 different investors.

The authors find a significant effect of geographical proximity and age similarity in explaining the probability that an investor finances a campaign. Moreover, these effects are particularly relevant if the proponent is located in areas characterized by a high risk of opportunistic behavior. Interestingly enough, they do not detect any significant effect related to gender.

In this paper, the authors have the unique opportunity to analyze a whole market (the Italian market) during three years, from inception (2013–2016), and to collect the identities of the investors in all successful campaigns.