Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

The power of positivity? The influence of positive psychological capital language on crowdfunding performance

We extend the entrepreneurship literature to include positive psychological capital — an individual or organization's level of psychological resources consisting of hope, optimism, resilience, and confidence — as a salient signal in crowdfunding. We draw from the costless signaling literature to argue that positive psychological capital language usage enhances crowdfunding performance. We examine 1726 crowdfunding campaigns from Kickstarter, finding that entrepreneurs conveying positive psychological capital experience superior fundraising performance. Human capital moderates this relationship while social capital does not, suggesting that costly signals may, at times, enhance the influence of costless signals. Post hoc analyses suggest findings generalize across crowdfunding types, but not to IPOs.     

The scope and scale of the informal food economy of South African urban residential townships: Results of a small-area micro-enterprise census

Growing urbanisation in South Africa is reflected in burgeoning Working class and informal township settlements on the fringes of its major towns and cities. Paired with this is an increasing reliance on cash as the primary means of economic transaction, which has in turn stimulated the growth of micro-enterprise business activities within the township context. This article discusses the findings of an eight-township small-area census which occurred between 2010 and 2013 in Cape Town, Johannesburg, Ekurhuleni and Durban townships representing 250 000 residents. The researchers were able to establish the scope and scale of informal food and drink retailing in these localities. Of the 10 049 micro-enterprises located in the study, some 3966 (or 39% of the total) trade in food. These include enterprises in primary production, fresh produce retailing, grocery retailing from house and spaza shops, and informal foodservice enterprises. Food is the basis for much township informal business and plays an important role in making food increasingly affordable and locally accessible, and in creating cash employment. The article builds on the knowledge base of the township informal economy role in bolstering food security needs for the marginalised.     

Cost Analysis of Calcium in Store Brand versus National Brand Grocery Products

Objective: This study was to determine if calcium fortification yields a higher price per serving in grocery store products. Researchers compared store brand to national brand grocery products in relation to cost in order to examine if calcium values were similar between store brand and national brand products. Methods: A total of 112 store brand and 211 national brand grocery products were collected from three low (national chain store), middle and high priced (Virginia and North Carolina regional store) grocery venues. Products were compared using price and calcium percentage per serving. ANOVA was used to determine between store brand and national brand for price per serving and calcium content, and between grocery venues. Results: National brand fortified products had a significantly lower mean price per serving when compared to national brand non-fortified products (p = 0.0002). There was no statistical difference between store brand fortified and non-fortified products (p = 0.9256). Low priced store brand products had the lowest mean price per serving ($0.34 ±0.24). Conclusions: This study found store brand products have similar calcium content as national brand products. Product cost was lower at low priced store compared to middle and high priced stores.     

Using performance-based warranties to influence consumer purchase decisions

Abstract

Traditional warranty analysis focuses on the reliability of a product and offers warranty designs that compensate a consumer if the item fails. We introduce the concept of a performance-based warranty (PBW) that guarantees that a product will operate at or above some baseline level of performance, such as a minimum energy efficiency for an appliance. We illustrate how consumer behavior can change in the presence of a PBW and define the parameters for which a manufacturer may increase revenue. Finally, we present an algorithm to solve for the optimal PBW design given a consumer’s belief about the expected performance of the product.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

COVID-19 and business renewal: Lessons and insights from the global airline industry

The emergence of the COVID-19 pandemic has adversely affected the fortunes of multiple companies around the globe. Accordingly, questions are increasingly being asked about how organizations can revitalize during and after a crisis. Yet, we have limited understanding of how organizations renew themselves during crises over time. We explore this question through the lens and examination of two South-Asian airlines: Pakistan International Airlines and Sri Lankan Airlines. The cases offer important insights into the reasons behind underperformance of state-controlled enterprises and renewal activities. We shed light on strategic renewal (SR) in the wake of increasing liberalization and deregulations in the global airline industry. To this end, we propose a four-stage approach towards renewing such underperforming organizations to respond effectively to black swan events and external shocks.     

Information flows and crashes in dynamic social networks

We develop a dynamic model of information transmission and aggregation in social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity, in which agents’ opinions are widely dispersed.