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In‐depth example of how TQM at a hospital in Memphis, Tennessee has reduced costs, decreased occupancy rates and generally improved efficiency and quality. Explores the possibilities of well‐defined TQM in the health care sector, highlighting the need for education, motivation and good communications and the success it has brought to this particular hospital.

As a rule, business books published today are backing off from lectures and theories, and are instead featuring more situation‐oriented illustrations of the basic concepts everyone already recognizes as right. What better place to get these anecdotes than from the horses' mouths? This batch gathers together the personal stories of top American business leaders, circa the late‐1990s, as told by themselves—with a little help from professional writers. The autobiographies represent hardcore, old‐fashioned industry (Lockheed), innovative industry (Nucor), service (Marriott), retail (Starbucks), and real estate/empire building (Trump).

The production, distribution and consumption of counterfeit goods have been increasing at an alarming rate. Current legislation addresses the supply side of the problem, but not the demand side of the problem. The purpose of this paper is to examine, empirically, factors affecting consumer demand for counterfeit goods were analyzed.

The economic theory of consumer demand provided the theoretical framework. Data were collected from students enrolled at a major mid‐western university, and logistic regression was used to estimate demand functions for counterfeit goods.

The results indicated that student sensitivity to the counterfeit problem did not significantly deter the purchase of counterfeit goods.

Educators in textiles and apparel should have a vested interest in providing education about counterfeiting, resulting in students with greater sensitivity to the issue.

The production, distribution and consumption of counterfeit goods have been increasing at an alarming rate. Current legislation addresses the supply side of the problem, but not the demand side of the problem. Consumer education may be a feasible approach for addressing the demand side of the problem.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

This paper aims to determine to what extent the housing affordability crisis is a “global” crisis and to what extent there is a variation across countries and over time, in who is concerned about housing affordability.

The author analyses data from about 500,000 respondents from over 140 countries and uses both descriptive statistics as well as regression analysis (using a random effects within between model [Bell et al., 2019]).

The findings show that concerns about housing affordability are widespread both within and across countries but the extent of these concerns depends greatly on the country, the subgroup and the indicator analysed. Moreover, in many countries, more people worry about other aspects of life than about housing affordability.

The global diversity in the housing affordability crisis suggests that one should be cautious when extrapolating research findings for a given country to other countries or when proposing housing policy transfer across countries.

The specific nature of the housing affordability crisis varies substantially across countries. Policymakers thus should be aware that there is no guarantee that a housing affordability policy that was effective in one country will also be effective in another country.

This paper is original in its use of the Gallup World poll, a unique survey, which is done world-wide and hence is ideally suited for the purpose of this paper, providing a much more detailed picture of the global housing crisis than so far available in the literature.

This paper aims to study network effects and the impacts on market structure in the specific context of China's network industries.

This paper is organized in the mode of “concept‐model analysis‐empirical examination”. Starting from the concept of “network effect”, it is then extended to the theoretical analysis of market structure and the examination of China's representative network industries.

The data for China's representative network industries produce mixed findings. Some prove the theoretical estimation quite well, while others do not follow the theoretical conclusion so closely.

The data for China's network industry are relatively limited. The depth of the data is especially inadequate, which prevents more systematic econometrical analysis.

The paper can serve as a reference for private decision makers of network industries and for regulators with antitrust concerns.

This paper may be the first of its kind to study the market structure of China's network industries from the perspective of network effects theory. It could be a good reference for those interested in learning the current status of China's network industries.

An ever-growing body of knowledge demonstrates the correlation among real-world phenomena and search query data issued on Google, as showed in the literature survey introduced in the following. The purpose of this paper is to introduce a pipeline, implemented as a web service, which, starting with recent Google Trends, allows a decision maker to monitor Twitter’s sentiment regarding these trends, enabling users to choose geographic areas for their monitors. In addition to the positive/negative sentiments about Google Trends, the pipeline offers the ability to view, on the same dashboard, the emotions that Google Trends triggers in the Twitter population. Such a set of tools, allows, as a whole, monitoring real-time on Twitter the feelings about Google Trends that would otherwise only fall into search statistics, even if useful. As a whole, the pipeline has no claim of prediction over the trends it tracks. Instead, it aims to provide a user with guidance about Google Trends, which, as the scientific literature demonstrates, is related to many real-world phenomena (e.g. epidemiology, economy, political science).

The proposed experimental framework allows the integration of Google search query data and Twitter social data. As new trends emerge in Google searches, the pipeline interrogates Twitter to track, also geographically, the feelings and emotions of Twitter users about new trends. The core of the pipeline is represented by a sentiment analysis framework that make use of a Bayesian machine learning device exploiting deep natural language processing modules to assign emotions and sentiment orientations to a collection of tweets geolocalized on the microblogging platform. The pipeline is accessible as a web service for any user authorized with credentials.

The employment of the pipeline for three different monitoring task (i.e. consumer electronics, healthcare, and politics) shows the plausibility of the proposed approach in order to measure social media sentiments and emotions concerning the trends emerged on Google searches.

The proposed approach aims to bridge the gap among Google search query data and sentiments that emerge on Twitter about these trends.

Studies five successful chief ’ntrepreneur officers (CNOs) together with one failure. Looks at why the CNO is indispensable. Presents 36 characteristics of CNOs across six groups: eagerly embracing risk, passionately innovating, creating/harnessing disequilibria, empowering the middle management, empowering top management with complementing industry product and participants and with complementing capital products and providers. Uses numerous case studies to demonstrate theory and provide a number of questions and answers.

This paper aims to present a multi-period dynamic power project financing model to produce pragmatic estimates of benchmark wholesale power prices based on the principles of normal profit. This, in turn, can guide policymakers as to whether price spikes or bidding above marginal cost in wholesale electricity markets warrants any investigation at all. One of the seemingly complex areas associated with energy-only wholesale electricity pools is at what point market power abuse is present on the supply side. It should not be this way. If a theoretically robust measure of normal profit exists, identification of potential market power abuse is straightforward. Such a definition readily exists and can be traced back to the ground-breaking work of financial economists in the 1960s.

Using a multi-period dynamic power project model, the authors produce pragmatic and theoretically robust measures of normal profit for project financed plant and plant financed on balance sheet. These model results are then integrated into a static partial equilibrium model of a power system. The model results are in turn used to guide policymaking on generator bidding in energy-only power markets.

Under conditions of perfect plant availability and divisibility with no transmission constraints, energy-only markets result in clearing prices which are not economically viable in the long run. Bidding must, therefore, deviate from strict short-run marginal cost at some stage. To distinguish between quasi-contributions to substantial sunk costs and market power abuse, a pragmatic and robust measure of normal profit is required.

This article finds policymakers can be guided by an ex-post analysis of base energy prices against pragmatic estimates for the long-run marginal cost of the base plant, and an ex-ante analysis of call option prices along the forward curve against pragmatic estimates of the carrying cost of the peaking plant.