Habitable Land Will Soon Become the World’s Scarcest Resource: Why Appalachia Should Choose Climate Change Havens over Millionaire Estates and Golf Courses

This research advocates for the construction of Climate Change Haven Communities across the Appalachian Region. The proposed development plan can be extended to the northern tier states across the US and also to the northern and mountainous regions of Europe and Asia. We present an analogy to the earlier climate change period of the Last Glacial Maximum/“Ice Age” in which these same northern regions of the planet were covered in ice sheets making them uninhabitable for most humans and many plant and animal species. In some significant ways, the Ice Age scenario can be a reverse-model for our current climate crisis. We also advocate strongly for the prevention of upscale real estate development projects in these same regions of the globe, as these will foreclose the possibility of safely sheltering the millions of persons who will be displaced by climate change over the next 5 to 10 years.

Social and Economic Considerations for Creating Sustainable Climate Change Haven Communities

As Climate Change Haven Communities are constructed across the Northern Hemisphere, it will be necessary to attract two types of migrants to populate them. The first group consists of professionals and companies in eco-sustainable businesses, such as law firms, insurance companies, investment firms, banking, technological innovation, mass media, medical research and pharmaceutical research. The second group will consist of persons engaged in organic/eco-sustainable agriculture whose crops and animal husbandry practices can be transferred successfully to Climate Change Haven regions. The present research focuses on the social and economic variables that must be taken into account to insure that each new Climate Change Haven Community becomes successfully integrated with the local population and forms a cohesive, harmonious social structure. Examples are given from the United States, France, Spain, Portugal and Italy.

A Markov-switching dynamic regression analysis of the asymmetries related to the determinants of US crude oil production between 1982 and 2019

The structural changes brought about by shale oil revolution have inspired this paper of which the aim is to analyze the potential asymmetries related to the determinants of crude oil production in the USA.Thus,using a Markov-switching dynamic regression model in which parameters change when oil production moves from one regime to the other,it is found that for both oil production and oil relative importance,the regime that was dominant during the 1980s and the early 1990s when oil production in the USA was substantially high is the same regime that has once again become dominant in the decade corresponding to the shale oil revolution.Furthermore,the study reveals the existence of asymmetries in the relationship between US crude oil production and both manufacturing production and the consumer price index.Asymmetries are also found in the relationship between the relative importance US crude oil and manufacturing production.Finally,it is found that the intercept and the variance parameter also vary from one regime to the other,thus justifying the use of regime-dependent models.

Promoting Climate Change Havens in the United States and Globally for Migrating Populations

Appalachia has been identified as the largest Climate Change Haven in the continental United States and could serve as a refuge for millions of persons. This research presents a marketing plan for promoting migration to the Appalachian Region using advertising and a website that communicates the desirable qualities of the area. Communications will first be directed toward the current residents of Appalachia (the Internal Market) in order to create enthusiasm for welcoming new arrivals. Then, promotional messages will be sent to prospective migrants seeking to escape the negative effects of climate change in the Southeast and Southwest of the United States and globally (the External Market). The approach used here may be applicable to Climate Change Havens across the globe.

Marketing Management for Consumer Products in the Era of the Internet of Things

In the Internet of Things (IoT) consumer products like coffee machines and smoke detectors are connected with the Internet, which effectively expands the Internet to the physical world. Such products have the ability to collect and share data from the user’s environment and, thus, their broad emergence will affect well-established concepts presented in the extant marketing literature. In order to provide a distinct contribution, we focus on customer relationship management, product life cycle management, as well as business model development and discuss implications of the enhanced capabilities of IoT products in these fields. By means of an extensive analysis of current developments in theory and practice, we systematically deduce ten research propositions. The paper concludes with a synthesis of findings and an outlook to promising directions for further research in IoT-oriented marketing management.

Wrong Use of Averages Implies Wrong Results from Many Heuristic Models

In a linear world, averages make perfect sense. Something too big is compensated by something too small. We show, however that the underlying differential equations (e.g. unlimited growth) rather than the equations themselves (e.g. exponential growth) need to be linear. Especially in finance and economics non-linear differential equations are used although the input parameters are average quantities (e.g. average spending). It leads to the sad conclusion that almost all results are at least doubtful. Within one model (diffusion model of marketing) we show that the error is tremendous. We also compare chaotic results to random ones. Though these data are hardly distinguishable, certain limits prove to be very different. Implications for finance can be important because e.g. stock prices vary generally, chaotically, though the evaluation assumes quite often randomness.

A bibliometric review of cryptocurrencies:how have they grown?

With the development of new technologies,some concepts become relevant in the economic area,as is the case with cryptocurrencies,in general,or Bitcoin and Ethereum,in particular.Due to the impact of these tools,a detailed bibliometric study that allows us to obtain all information about cryptocurrencies must be conducted.This study will help scientific production by specifying the development and lines of related research that have been followed and are currently being followed.We have used Tableau,R(Bibliometrix R Package),and VOSviewer software to analyze the information.These have been combined to create and review unified metadata from the Web of Science(WoS)and Scopus databases.The bibliometric analysis shows 771 articles on the WoS database and 648 articles on Scopus published between 2010 and early 2019.They present the most relevant articles,research areas,countries,institu-tions,authors,journals,and trends during the last few years.In conclusion,the number of publications has grown in the last 3 years.The analysis shows the evolution of block-chain technology used in this type of cryptocurrency.The review of this period marks a possible end to the historical part of cryptocurrencies,thereby opening the current topic to its multiple applications.

Scrutinizing Distributions Proves That IQ Is Inherited and Explains the Fat Tail

The motivation of this paper is to show how to use the information from given distributions and to fit distributions in order to confirm models. Our examples are especially for disciplines slightly away from mathematics. One minor result is that standard deviation and mean are at most a more or less good approximation to determine the best Gaussian fit. In our first example we scrutinize the distribution of the intelligence quotient (IQ). Because it is an almost perfect Gaussian distribution and correlated to the parents’ IQ, we conclude with mathematical arguments that IQ is inherited only which is assumed by mainstream psychologists. Our second example is income distributions. The number of rich people is much higher than any Gaussian distribution would allow. We present a new distribution consisting of a Gaussian plus a modified exponential distribution. It fits the fat tail perfectly. It is also suitable to explain the old problem of fat tails in stock returns.

Covariance Estimation Using High-Frequency Data： An Analysis of Nord Pool Electricity Forward Data

The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM （Capital Asset Pricing Model betas）, derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution （both distributional properties and temporal dependencies） of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.

Like a Sum Is Generalized into an Integral, a Product May Be Generalized into an Inteduct

It is well known that an integral is nothing but a continuous form of a sum. Is it possible to do the same thing with a product? The answer is yes and done for the first time in this publication. The new operator is called inteduct. As an integral is a proper tool to calculate the arithmetic mean of a function, the inteduct gives the geometric mean of a function. This defines a new branch of mathematics. Most applications may lay way ahead. Only some are discussed here. One is applying the inteduct to probability theory. There it is possible e.g., to determine a function for a life expectation rather than just a numerical value. Another application is to distinguish chaos from randomness within numerically given values. At least for the logistic map there exists a direct connection between Lyapunov exponent and inteduct. To distinguish between chaos and randomness is particularly important in finance. While randomness implies ergodicity, chaos is non-ergodic. And many fundamental financial theories from portfolio theory to market efficiency require ergodicity.

A PATH ANALYTICAL ANALYSIS OF ORGANIZATIONAL INTEGRATION PRACTICES'EFFECTS ON MANUFACTURING FLEXIBILITY AND COMPETITIVE ADVANTAGF

To cope with an increasingly turbulent environment, manufacturing firms increasingly implement integration practices to enhance flexibility in the production process. This research develops a framework to explore the relationships among organizational integration practices, manufacturing flexibility, and competitive advantage. The study develops valid and reliable instruments to measure these constructs, and it applies structural equation modeling to test relationships among these variables using a large sample. The results indicate strong, positive, and direct relationships between organizational integration practices and manufacturing flexibility, and between manufacturing flexibility and competitive advantage. The results also indicate that organizational integration practices enhance competitive advantage directly as well as indirectly by facilitating manufacturing flexibility.

MIP FORMULATIONS AND HEURISTICS FOR SOLVING PARALLEL BATCHING PROBLEMS

This paper addresses the scheduling problem involving batch processing machines, which is Mso known as parallel batching in the literature. The presented mixed integer programming formulation first provides an elegant model for the problem under study. Fhrthermore, it enables solutions to the problem instances beyond the capability of exact methods developed so far. In order to alleviate computational burden, the authors propose MIP-based heuristic approaches which balance solution quality and computing time.