Introducing E-MARKPLAN: A practical methodology to plan e-marketing activities

Although e-marketing is highly prevalent, no template currently exists for managers who wish to use the Internet/Web and related information technologies to market their products and services. This paper provides managers with a comprehensive, actionable, and practical methodology (E-MARKPLAN) to plan, enact, and analyze e-marketing activities. Five case studies are used to illustrate the diversity of e-marketing actions. E-MARKPLAN consists of five parts: goals, actors (i.e., those who take e-marketing actions), spaces (i.e., theaters of engagement), actions, and outcomes. The E-MARKPLAN methodology is versatile, and is not limited to companies which have e-commerce operations.     

Exchange and refund of complementary products

A common dilemma a consumer faces during product return pertains to the decision of exchanging the product or obtaining a refund. This issue becomes even more salient for durable goods, when the initial purchase involves complementary products from different categories. This research examines consumer’s trade-off decision between returning and keeping complementary products by exploring various retail actions (using umbrella branded products (UBP)) and customer characteristics. We also investigate the trade-off between product exchange and refund when consumer returns a product. We find interesting extensions to past research wherein UBP are returned less and result in greater exchange than refund. Furthermore, an interesting caveat is that higher degree of complementarity between UBP intensifies the impact of various factors on exchange as opposed to refund of products. Implications for retail managers and sales teams are explored.     

The empirical validity of the New Keynesian Phillips curve using survey forecasts of inflation

This paper investigates the performance of the New Keynesian Phillips curve when survey forecasts of inflation are used to proxy for inflation expectations. Previous authors such as Brissimis and Magginas (2008) have applied survey measures of inflation expectations to the NKPC, and have concluded that these estimates are superior to those estimated using actual data on future inflation. However this approach employs the use of the labor income share as the proxy for real marginal cost, something which is highly problematic once we consider the countercyclicality of this variable. This paper develops and tests a procyclical marginal cost variable alongside various survey measures of inflation forecasts in the NKPC, while recognizing the problem of weak instruments that occurs when estimating the model using conventional GMM. We find that the NKPC produces a counter-intuitive negative and significant coefficient on procyclical marginal cost when surveys of inflation forecasts are used, which casts serious doubt on the empirical viability of the NKPC model, even when estimated with survey inflation forecasts.     

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.     

Interactive Technologies and Retailing Strategy: A Review,Conceptual Framework and Future Research Directions

During the past decade, a number of interactive technologies, including the Internet, have fundamentally transformed how retailers compete in the marketplace. In a similar vein, emerging interactive technologies can be expected to significantly alter the retailing landscape through their impact on retailing strategy and operations. Furthermore, it is conceivable that certain emerging interactive technologies will be perceived by some retailers as enablers (tools to more effectively compete in the marketplace) and by other retailers as disruptors of the present ways of doing business. Interactive technologies can either be generic, a technology that is readily available from an information technology (IT) vendor and is widely adopted by retailers, or proprietary. An interactive technology that is proprietary can enable a firm to generate economic rents from the innovation for an extended duration of time. Investing in a generic interactive technology, however, may be perceived as a cost of doing business for a retailer, and not a potential source of sustainable competitive advantage. However, a retailer's complementary resource endowments may enable the retailer to more effectively leverage a generic technology relative to its competitors and thereby achieve a sustainable competitive advantage. In this paper, we review the related literature, develop a process model delineating the mechanisms by which an interactive technology can affect and necessitate changes in retailers' strategies and identify directions for future research.     

Staged investments in entrepreneurial financing

Venture capitalists deliver investments to entrepreneurs in stages. This paper shows staged financing is efficient. Staging lets investors abandon ventures with low early returns, and thus sorts good projects from bad. The primary implication from staging is that it is efficient to invest more in later rounds. The model yields a number of predictions on how the ratio of early to late round financing varies with uncertainty, the outside options of both parties, the value of the venture, the costs of investment, and project difficulty. We test these predictions against data on venture capital financings and find significant empirical support for the theory.     

Firm Opacity Lies in the Eye of the Beholder

We classify and test empirical measures of firm opacity and document theoretical and empirical inconsistencies across these proxies by testing the relative opacity of banks versus non‐banks. We evaluate the effectiveness of these proxies by observing the effect of two cleanly identified shocks to firm‐specific information: credit rating initiation and inclusion in the S&P 500 index. Using a difference‐in‐difference approach, we compare firms that are newly rated and firms that are included in the S&P 500 index with a propensity matched sample of “unchanged” firms. We find that only the number of analysts and Amihud's illiquidity ratio provide consistent patterns across different estimation specifications and different econometric settings. These two proxies show that banks are more opaque than non‐banks. Based on our tests, we recommend that these proxies be used as the primary measures of firm opacity.     

Persistent gaps and default traps

We show how vicious circles in countries' credit histories arise in a model where output persistence is coupled with asymmetric information about output shocks. In such an environment, default signals the borrower's vulnerability to adverse shocks and creates a pessimistic growth outlook. This translates into higher interest spreads and debt servicing costs relative to income, raising the cost of future repayments, thereby creating “default traps”. We build a long and broad cross-country dataset to show the existence of a history-dependent “default premium” and of significant effects of output persistence on sovereign creditworthiness, consistent with the model's predictions.