Customer satisfaction with socially responsible investing initiatives: The influence of perceived financial and non-financial quality

During the last decade, socially responsible investment (SRI) initiatives have grown to become a mainstream financial service in many countries. However, to date, only a few studies focus on understanding the final investor of such initiatives. This article focuses on one particularly overlooked aspect of SRI behavior; that of customer post-purchase satisfaction. A theoretical model of satisfaction with SRI-profiled mutual funds is developed and tested. The results indicate that perceived financial performance of the SRI-profiled mutual fund is the most important predictor of customer satisfaction. However, perceived environmental, social and governance (ESG) performance also had a positive impact on satisfaction for the SRI mutual fund. On the basis of these results, it is argued that although ESG quality is important to customers, marketers of SRI initiatives should primarily focus on the conventional quality attributes such as financial performance, as a good ESG record alone is unlikely to generate customer satisfaction.     

Instability in cointegration regressions: a brief review with an application to money demand in Portugal

This study addresses some modelling questions related to the possibility of structural change in models with nonstationary variables. Focusing on cointegration issues, some methodological aspects are discussed, attempting to integrate coherently the several steps of the modelling strategy. These range from unit root to cointegration testing and to testing for instability in the cointegration vector. An empirical example with Portuguese data tries to illustrate the usefulness of this approach, where a simple money demand function is estimated using an error-correction model (ECM). If a break is explicitly allowed in the cointegration vector the forecasting performance of the ECM improves.     

Urban bicycle tourism: path dependencies and innovation in Greater Copenhagen

Abstract

During the latest decade, a renaissance of bicycling in urban transportation has occurred in many Western European cities. This opens up for a development of bicycle tourism as a form of urban sustainable tourism, taking advantage of improved infrastructure and facilities for cycling tourists. The aim of this study is to conceptualise the dynamics behind the development of urban bicycle tourism. This development may be viewed as an innovative process based on incremental changes in local socio-technological mobility systems. An analytical framework is proposed, based on the following categories: urban planning, bicycle tourism services, communication, and place making. In the analysis, evidence from the Greater Copenhagen region is used to contextualise particularly these perspectives of the development of urban bicycle tourism. In each of the four categories, evidence of innovative services or procedures supporting bicycle tourism was found. However, the most important source of incremental innovation is likely to be found on a systemic level, between the actors in the destination. It is also argued that the development of urban bicycle tourism is highly path dependent, related to the local bicycle culture. Bicycle tourism should not be viewed as isolated from the locals’ everyday cycling.     

Power mapping with dynamical adjustment for improved portfolio optimization

For financial risk management it is of vital interest to have good estimates for the correlations between the stocks. It has been found that the correlations obtained from historical data are covered by a considerable amount of noise, which leads to a substantial error in the estimation of the portfolio risk. A method to suppress this noise is power mapping. It raises the absolute value of each matrix element to a power q while preserving the sign. In this paper we use the Markowitz portfolio optimization as a criterion for the optimal value of q and find a K/T dependence, where K is the portfolio size and T the length of the time series. Both in numerical simulations and for real market data we find that power mapping leads to portfolios with considerably reduced risk. It compares well with another noise reduction method based on spectral filtering. A combination of both methods yields the best results.     

An approximate distribution of delta-hedging errors in a jump-diffusion model with discrete trading and transaction costs

We introduce a jump-diffusion model for asset returns with jumps drawn from a mixture of normal distributions and show that this model adequately fits the historical data of the S&P500 index. We consider a delta-hedging strategy (DHS) for vanilla options under the diffusion model (DM) and the proposed jump-diffusion model (JDM), assuming discrete trading intervals and transaction costs, and derive an approximation for the probability density function (PDF) of the profit-and-loss (P&L) of the DHS under both models. We find that, under the log-normal model of Black–Scholes–Merton, the actual PDF of the P&L can be well approximated by the chi-squared distribution with specific parameters. We derive an approximation for the P&L volatility in the DM and JDM. We show that, under both DM and JDM, the expected loss due to transaction costs is inversely proportional to the square root of the hedging frequency. We apply mean–variance analysis to find the optimal hedging frequency given the hedger's risk tolerance. Since under the JDM it is impossible to reduce the P&L volatility by increasing the hedging frequency, we consider an alternative hedging strategy, following which the P&L volatility can be reduced by increasing the hedging frequency.     

Organizational culture and post-acquisition changes in management control systems: An analysis of a successful Brazilian case

This paper analyzes the effect of organizational culture on the post-acquisition management control system (MCS) of the Brazilian company Extrativa Metalquímica Inc. after its acquisition by the FASA Participações Group. The results herein reported add to discussions of the subject and contribute to reducing the research gap in this area in Brazil. The analysis supports two major conclusions: (1) changes in the acquired company's MCS were derived from the new financial results-oriented culture introduced by the acquirer; and (2) the implementation of this culture implied modifications in production, financial and quality controls.     

Effects of rent dependency on quality of government

This paper introduces quality of government rather than regime type as dependent variable in studies of political effects of natural resources. It consists of two parts. First, it argues for an effect of fiscal dependency of oil and gas rents on quality of government. Second, it finds significant, negative effects of oil and gas rent dependency on three empirical indicators of quality of government—low corruption, bureaucratic quality and legal impartiality—in a sample of 139 states in the period 1984–2006. The results hold for inclusion of control variables such as regime type, income, region and religion.     

Deterministic seasonality in Dickey–Fuller tests: should we care?

This paper investigates the properties of Dickey–Fuller tests for seasonally unadjusted quarterly data when deterministic seasonality is present but it is neglected in the test regression. While for the random walk case the answer is straightforward, an extensive Monte Carlo study has to be performed for more realistic processes and testing strategies. The most important conclusion is that the common perception that deterministic seasonality has nothing to do with testing for the long-run properties of the data is incorrect. Further numerical evidence on the shortcomings of the general-to-specific t-sig lag selection method is also presented.

Children’s interactions with technology in teachers’ self-reported activities in Sweden’s preschools

International Journal of Technology and Design Education - This study investigates preschool children’s interactions with technology in a Swedish context. The purpose is to broaden our...     

Human–machine trans roles conflict in the organization: How sensitive are customers to intelligent robots replacing the human workforce?

In organizations facing digital transformation, intelligent technologies are starting to replace the human workforce. At present, managers delegate tasks to an artificial agent and rarely consider the customer reception of such decisions. This arouses tensions between the main stakeholders of the organization. This paper shows that the rash adaptation of the digital workforce may be perceived as an irresponsible innovation that brings negative consequences for companies. If a task is regarded by customers as dedicated to humans, and managers delegate it to machines, a new type of conflict – human-machine trans roles conflict (HMTRC), appears. This paper intends to show that customers are sensitive to HMTRC. This research uses quantitative methods and consists of three stages. First, people were asked to indicate which tasks in an organization should be performed by (a) humans and (b) machines. According to these results, two leaflets for customers were designed (low vs. high HMTRC). In the second stage, standard procedures were used to construct a scale measuring customer reactions to HMTRC on three dimensions: cognitive, emotional and behavioural. Ultimately, the scale and two leaflets were used to check how customers react to different intensities of HMTRC. The research results show that customers are aware when HMTRC occurs and perceive it negatively (cognitive response). Moreover, it evokes negative emotions (emotional response) and prompts customers to take action against the company in which this conflict takes place (behavioural response). The practical contribution of this research is the three-dimensional scale. It may predict customers' reactions to task delegation with different intensities of HMTRC and help build a technologically sustainable organization.