A story to sell: The influence of storytelling on consumers' purchasing behavior

Storytelling can arouse consumers' emotions and affect purchasing behavior through desires and attitudes. While the marketing literature discusses storytelling, there is a lack of consensus because of the diverse conceptual and operational definitions used. To untangle the complexities and consolidate the fragmented knowledge about storytelling in marketing, this research examines how the marketing literature has addressed the influence of storytelling on consumers' purchasing behavior. The findings aid in understanding how the topic has been discussed from a marketing perspective in consumer behavior studies. Through a systematic literature review using a bibliometric analysis, we demonstrate that the marketing literature features four strands about the uses of storytelling to influence consumers' purchasing behavior. First, storytelling stimulates the consumer's identification with the brand. Second, storytelling allows consumers to experience emotional value. Third, storytelling supports engagement behaviors. Finally, storytelling has a downside in that it also propagates harmful speech. This study concludes with a roadmap for future research about how storytelling impacts consumers' purchasing behavior.     

U-Convolutional model for spatio-temporal wind speed forecasting

The increasing penetration of intermittent renewable energy in power systems brings operational challenges. One way of supporting them is by enhancing the predictability of renewables through accurate forecasting. Convolutional Neural Networks (Convnets) provide a successful technique for processing space-structured multi-dimensional data. In our work, we propose the U-Convolutional model to predict hourly wind speeds for a single location using spatio-temporal data with multiple explanatory variables as an input. The U-Convolutional model is composed of a U-Net part, which synthesizes input information, and a Convnet part, which maps the synthesized data into a single-site wind prediction. We compare our approach with advanced Convnets, a fully connected neural network, and univariate models. We use time series from the Climate Forecast System Reanalysis as datasets and select temperature and u- and v-components of wind as explanatory variables. The proposed models are evaluated at multiple locations (totaling 181 target series) and multiple forecasting horizons. The results indicate that our proposal is promising for spatio-temporal wind speed prediction, with results that show competitive performance on both time horizons for all datasets.     

Executive Compensation： Pay-for-Performance in High-Technology Firms

This study examines the relationship between corporate performance and the Chief Executive Officer （CEO） compensation in high-technology firms in the S＆P 500. The total short- and long-term CEO compensation in high-technology was compared with other industrial sectors from standard classification codes and tested in terms of corporate performance. The ExecuComp database was used to find the variables and to create a sample of firms between 2004 and 2010. Important corporate performance variables are used in this work, such as assets, employees, sales, net income, and earnings per share （EPS）, as reported by the firms for each year. A panel data GLS with a fixed effect model for time is estimated that describes total compensation for the period between 2004 and 2010. The result was aligned with the theory of executive compensations to address agency problems and to examine CEO pay-for-performance. The main objective of this paper is to consistently demonstrate that the performance is determined for the total CEO compensation for short- and long-term periods and to examine whether the total remunergttion paid to CEOs in high-technology firms in the S＆P 500 is related to corporate finance. This work provides a better understanding of the relationship between compensation and performance in high-technology firms. Results suggest that high-tech firms tend to use more sophisticated performance measurements to determine CEO compensation.     

The Stability of Social Preferences in a Low‐Income Neighborhood

We investigate whether social preferences are stable across contexts using a field population of low‐income Americans. We develop and demonstrate a simplified, visually‐based experimental methodology appropriate for this population. We show that choices in a laboratory public goods game predict giving in real donation experiments, as well as self‐reported donations and volunteering outside the lab. At the same time, choices vary systematically by individual characteristics and decision context. Thus, our results provide evidence both for an underlying stable social preference and for the role of context in influencing the expression of that preference.     

Reflections on the perspectives of the global economy from the point of view of emerging economies

 Recently a number of emerging economies, with high inflation and various kinds of imbalances have experienced what has come to be referred to as dollarization– the phenomenon of currency substitution where the dollar gradually replaces the national currency in the performance of its fundamental functions. The phenomenon is most commonly encountered as a component of the exchange-rate-based stabilization programs implemented in a number of emerging economies in Latin America, Asia and the Middle East. The fundamental issue we want to explore is whether this process forces the monetary authorities of emerging economies to act with their hands tied, as if caught in a trap. It is argued that when the expansion of liquidity and domestic credit is determined by the quantity of foreign-exchange reserves, an independent monetary policy vanishes and national sovereignty itself is shackled. Since this scenario typically occurs in a world of increasing globalization of finance, this paper also discusses (with reference to emerging economies) the risks and implications of capital inflows for macroeconomic policy autonomy, economic instability, and vulnerability to external shocks.     

Distributing the Benefits from the Commons: A Square-Root Formula

What should be the distribution of the benefits of a fishery (or common-pool resource) where a group of fishers catch fish and sell it to consumers? I propose that, for each person i, where i is a fisher or a consumer, i's returns should be proportional to i's contributions. Unexpectedly, this implies that the fraction of benefits accruing to consumers must be √value of total output of fish/√value of total outputs of fish+√value of total fishers' labor.     

Towards a ‘progressive mediation approach’ in planning

This article is concerned with planning for the ‘disadvantaged’, a term defined in the main text. It is argued that the prevailing planning approach in South Africa is inadequate for dealing with present social realities. A more socially relevant approach, the ‘Progressive Mediation Approach’, derived from an analysis of mediation theory, is proposed. For ease of analysis and argument the article focuses on the urban scale and on the discipline of Town and Regional Planning but its relevance to other disciplinary forms of planning is evident.     

The role of mental health and addiction among high-cost patients: a population-based study

Aims: Previous work found that, among high-cost patients, those with a majority of mental health and addiction (MHA)-related costs (>50%) incur over 30% more costs than other high-cost patients. However, this work did not examine other high-cost patients in depth or whether they had any MHA-related costs. The objective of this analysis was to examine the role of MHA-related care among other high-cost patients.

Methods: Using administrative healthcare data from Ontario, Canada, this study selected all patients in the 90th percentile of the cost distribution in 2012. It focused primarily on two groups based on the percentage of MHA-related costs relative to total costs: (1) high-cost patients with some MHA-related costs (0%?>?and <50%) and (2) high-cost patients with no MHA-related costs (0%). We examined socio-demographic and clinical characteristics, utilization and costs for both groups, and modeled patient-level costs using appropriate regression techniques. We also compared these groups with high-cost patients with a majority of MHA-related costs (>50%).

Results: High-cost patients with some MHA-related costs incurred over 40% more costs than those without ($27,883 vs $19,702). Patients with some MHA-related costs were older, lived in poorer neighborhoods, and had higher levels of comorbidity compared to those without. After controlling for relevant variables, having any type of MHA-related utilization increased costs by $2,698. Having a diagnosis of psychosis had a large impact on costs.

Limitations: This study did not examine children and adolescents. We were only able to account for 91% of all costs incurred by the public third-party payer; addiction-related costs from community-based agencies were not available.

Conclusions: High-cost patients with MHA incur higher costs compared to those without. When considering interventions aimed at high-cost patients, policy-makers should consider their complex nature, specifically both their physical and MHA-related comorbidities.