Sustainability of A Pay‐as‐you‐Go Pension System in A Small Open Economy with Ageing,Human Capital and Endogenous Fertility

The aim of the article is to theoretically investigate if a pay‐as‐you‐go (PAYG) pension system is sustainable in the presence of a declining population and increasing longevity of the retired generation. For this purpose, we use an overlapping generation model with endogenous fertility, endogenous longevity and human capital accumulation in a small open economy. We find that pensions will always increase as long as it is beneficial for parents to invest in human capital. Furthermore, we get the result that the ratio between pension benefits and the consumption of the young generation will strive to a positive limit value, and that a pure PAYG pension system will not run into any solvency problem due to a decreasing fertility rate or ageing.     

Conceptualizing the Evolution and Future of Advertising

Technology has irreversibly changed the way that firms identify who is more likely to buy, what they are more likely to buy, when they are more likely to buy, why they are likely to buy, and how they are likely to buy, repurchase, and recommend. It is now easier than ever for firms to have a body of evidence in the form of actual insights, as opposed to having mere guestimates, on consumers' apparent intentions to buy. Power dynamics have changed in the marketing climate, and firms have to factor in not only aggressive competitors but also empowered customers with limited attention spans. In such a climate, what lies in the future for advertising? And how can marketing managers make the most of the changing climate and maximize their returns on advertising? How can academics advance research related to maximizing the effectiveness and efficiency of advertising? These are the questions that this article addresses via an integrated framework that expounds all the factors related to customers, firms, technological environment, and data resources, as well as the contextual factors, including product life cycle, customer life cycle, and so on, and their collective impact on advertising strategy, which includes advertising content, media selection, message, and targeting.     

Effects of Mood and Elaboration on Processing and Evaluation of Goal‐Framed Appeals

Two experiments examined the influence of mood and elaboration on consumer processing and evaluation of goal‐framed appeals. Subjects displayed more favorable attitudes and purchase intent (PI) when exposed to negative goal frames than equivalent positive ones. These effects were attenuated under high‐elaboration conditions. Compared to subjects in positive moods, those in negative moods exhibited more favorable thoughts, attitudes, and PI toward negative goal frames. Finally, mood and frame valence did not affect depth of processing but had a consistent impact on style of processing, that is, positive frames and moods induced relational processing whereas negative frames and moods engendered item‐specific processing.     

Changing Contours of Income Stratification and Decomposition of Income Inequality: Evidence from Recent Longitudinal Survey in India

The paper, based on India Human Development Survey (IHDS) data, tries to address the question- how unequal is India in terms of income distribution? Accordingly, the paper examines the trends, levels, sources and factors of income inequality in India between 2005 and 2012. Three important results stemmed from our analysis. First, in this paper we use Gini as a measure of inequality and find that income inequality in rural India has increased from 0.50 to 0.54 between 2005 and 2012, whereas, in urban India income inequality has increased from 0.48 to 0.49 during the same period. Next and most importantly, we decompose income inequality by income sources and find that amongst different sources of income inequality; the contribution of farm income in total inequality has decreased from 35 percent in 2005 to 21 percent in 2012 in rural India. On the other hand, the contribution of salaried income in total inequality has plummeted drastically from 65 percent in 2005 to 16 percent in 2012 in urban India. Finally, we use Theil’s T index from the class of Generalized Entropy (GE) inequality measures, while decomposing income by four most important factors; namely, place of residence, social, educational and occupational groups. It is irrespective of these factors; the relative share of within-group inequality is not only much higher than that of between-group inequality, also its share has increased between these two periods. Thus, our paper suggests that these mutually reinforcing inequalities, in the long run, if not addressed effectively, will create a hard-hitting division between the privileged and the rest in Indian society.

     

Building the BoP Producer Ecosystem: The Evolving Engagement of Fabindia with Indian Handloom Artisans

Recent research on the base of the pyramid (BoP) has called on firms to initiate market‐driven interventions directed at the BoP population with the objective of identifying and pursuing mutually profitable means of attaining meaningful poverty alleviation outcomes. In response, firms as well as scholars have engaged at length with the creation of new products and services for the BoP consumer but paid far less attention to the BoP producer—a member of the BoP population who creates value by producing goods and services for sale in nonlocal markets. Additionally, extant studies have largely focused on snapshot views of BoP interventions by firms, thereby limiting our understanding of the emergence of meaningful poverty‐alleviating outcomes over time from these interventions. This paper seeks to redirect attention toward the dynamic of the long‐term engagement between the firm and the BoP producer. Using rich qualitative data from Fabindia—an Indian handloom retailer—this paper examines how the engagement between Fabindia and communities of handloom artisans in India has persisted over a period of five decades. We found that, even as it encountered changes in the external environment and pursued newer organizational goals, Fabindia repeatedly renewed its engagement with handloom artisans and facilitated progression in poverty‐alleviation outcomes. Building on the insights from the case study, this paper presents a process model that highlights the role of innovative management practices in sustaining engagements between firms and BoP producers over time. Additionally, this paper proposes the concept of the “bridging enterprise”—a business enterprise that originates at the intersection of specific BoP communities and the corresponding nonlocal markets—as an interpreter and innovator reconciling the interests of stakeholders across the pyramid.     

Researches in Corporate Social Responsibility: A Review of Shifting Focus,Paradigms, and Methodologies

Owing to the growing academic and practitioner’s interest in the field of Corporate Social Responsibility, there is a need to do a comprehensive assessment and synthesis of research activities. This article addresses this need and examines the academic literature on Corporate Social Responsibility and Performance using a paradigmatic and methodological lens. The objective of this article is fourfold. First, it examines the status of CSR research from its beginning especially after 1970 to year 2008 in leading academic journals and reports to assess the focus areas of research on CSR so far. Second, it analyzes the research paradigms adopted in these research articles using the Operations Research Paradigm framework. Third, it compares and contrasts various kinds of research articles, methodologies, and research designs used in various researches in literature. Finally, it uncovers the implications of this study and directions for future research.     

Order Flows,Investor Sentiments and Feedback Trade in Index Futures Market

This paper examines the presence of feedback trading, and investor sentiment drove feedback trading by traders in the Nifty 50 index futures contract in India. The results of the study using high-frequency data sampled at 10 min interval using VAR and contemporaneous VAR model as applied to market microstructure settings reveals negative evidence of feedback trade and investor sentiment-driven feedback trade in Nifty 50 futures contract. Further, consistency with noise trading hypothesis, order flows in Nifty 50 futures contract is less informative when traders are overly optimistic.

     

Predicting Internet banking adoption in India: a perceived risk perspective

The emergence of Internet banking has transformed the banking systems across the globe. As a channel to market, Internet banking allows geographical constraints to be overcome by offering various products and services at lower customer costs. An understanding of the factors influencing customer adoption of Internet banking is both relevant and timely. This study integrates technology acceptance model and perceived risk theory in understanding Internet banking acceptance among Indian bank account holders. Specifically, this study categorizes perceived risk as external risk and internal risk, and examines its influence on customer beliefs and adoption of Internet banking. Using two-step predictive analytics of structural equation modeling and artificial neural network analysis, the 270 responses reveal that both external risk and internal risk inhibit customer acceptance of Internet banking. More importantly, neural network analysis reveals that perceived ease of use and external risk are two important factors determining how well Internet banking is accepted by customers. The implications of the study findings and future research directions are presented.     

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.     

An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing

Zika virus is a mosquito-borne disease that spreads very quickly in different parts of the world. In this article, we proposed a system to prevent and control the spread of Zika virus disease using integration of Fog computing, cloud computing, mobile phones and the Internet of things (IoT)-based sensor devices. Fog computing is used as an intermediary layer between the cloud and end users to reduce the latency time and extra communication cost that is usually found high in cloud-based systems. A fuzzy k-nearest neighbour is used to diagnose the possibly infected users, and Google map web service is used to provide the geographic positioning system (GPS)-based risk assessment to prevent the outbreak. It is used to represent each Zika virus (ZikaV)-infected user, mosquito-dense sites and breeding sites on the Google map that help the government healthcare authorities to control such risk-prone areas effectively and efficiently. The proposed system is deployed on Amazon EC2 cloud to evaluate its performance and accuracy using data set for 2 million users. Our system provides high accuracy of 94.5% for initial diagnosis of different users according to their symptoms and appropriate GPS-based risk assessment.