A hybrid machine learning model for forecasting a billing period’s peak electric load days

Many models have been studied for forecasting the peak electric load, but studies focusing on forecasting peak electric load days for a billing period are scarce. This focus is highly relevant to consumers, as their electricity costs are determined based not only on total consumption, but also on the peak load required during a period. Forecasting these peak days accurately allows demand response actions to be planned and executed efficiently in order to mitigate these peaks and their associated costs. We propose a hybrid model based on ARIMA, logistic regression and artificial neural networks models. This hybrid model evaluates the individual results of these statistical and machine learning models in order to forecast whether a given day will be a peak load day for the billing period. The proposed model predicted 70% (40/57) of actual peak load days accurately and revealed potential savings of approximately USD $80,000 for an American university during a one-year testing period.     

Optimal rebalance rules for the constant proportion portfolio insurance strategy – Evidence from China

The constant proportion portfolio insurance (CPPI) strategy is one of the most popular asset allocation strategies employed by guaranteed-return financial products investors. Rebalance disciplines play an important role in determining the CPPI performance in practice. This paper examines whether the selection of rebalance rules affects CPPI strategy performance in the context of Chinese equity markets and, if so, in what pattern, and whether an optimal parameter of rebalance exists. We find that, (1) the three alternative rebalance disciplines – time discipline, market move discipline and lag discipline – are indifferent in affecting the performance of CPPI strategy; (2) in terms of optimal parameters of each rebalance rule, the optimal rebalancing period for the time discipline is 3 trading days, the optimal trading threshold of the market move discipline 4%, and the optimal lag factor of the lag discipline 6%. These optimal parameters are not influenced by the length of investment.     

Management by objectives – an effective tool for teamwork?

In recent years many companies have introduced self-regulatory teamwork requiring changes in leadership behaviour and systems as well. Consequently a renewed interest has arisen in management by objectives (MBO) as a means for leading self-regulating teams. But how do MBO systems work and how effective are they? The MBO system of a company in the construction supply industry was analysed. This company had implemented MBO at team level five years ago. In order to explore the mechanisms and effects of MBO at team level a model for group goal setting was tested. One hundred and seventy-six employees in twenty-six teams participated in the study, but only twenty-one groups having objective productivity data were included in the analyses at team level. Group goal commitment and group goals moderated by task interdependence are supposed to influence group processes as a mediating variable for group effectiveness. Results do not consistently support this model. Group goals and goal commitment predict group productivity and job satisfaction but group processes mediate only the relationship to job satisfaction. The moderating effect of task interdependence could not be supported. The consequences for developing a model for MBO at team level and implementing effective MBO systems are discussed.     

Affordable dwelling-layout system design—A model for optimization

The systems nature of the residential land planning has been outlined and an optimization model for minimizing the cost of a layout has been presented earlier. In the present paper, a model for optimal design of the dwelling-layout system, consisting of the dwelling as well as the residential layout, has been developed. In this model, which is also a non-linear programming problem, maximizing the dwelling space has been taken as the objective function. Affordable cost and physical design standards such as density, public open space, circulation interval, have been taken as the constraints in the model. The problem has been solved using the geometric programming technique and the programme developed by the author. Using this model, a dwelling-layout system could be designed directly to achieve the maximum benefit i.e. maximum dwelling space, within the given affordable cost and fulfilling the given physical design standards mentioned above.     

A Bayesian mixed logit–probit model for multinomial choice

In this paper, we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumption-free nonparametric density specification, while other alternative-specific coefficients are assumed to be drawn from a multivariate Normal distribution, which eliminates the independence of irrelevant alternatives assumption at the individual level. A hierarchical specification of our model allows us to break down a complex data structure into a set of submodels with the desired features that are naturally assembled in the original system. We estimate the model, using a Bayesian Markov Chain Monte Carlo technique with a multivariate Dirichlet Process (DP) prior on the coefficients with nonparametrically estimated density. We employ a “latent class” sampling algorithm, which is applicable to a general class of models, including non-conjugate DP base priors. The model is applied to supermarket choices of a panel of Houston households whose shopping behavior was observed over a 24-month period in years 2004–2005. We estimate the nonparametric density of two key variables of interest: the price of a basket of goods based on scanner data, and driving distance to the supermarket based on their respective locations. Our semi-parametric approach allows us to identify a complex multi-modal preference distribution, which distinguishes between inframarginal consumers and consumers who strongly value either lower prices or shopping convenience.     

Cross-section dependence and the monetary exchange rate model – A panel analysis

This paper tackles the issue of cross-section dependence for the monetary exchange rate model in the presence of unobserved common factors using panel data from 1973 until 2007 for 19 OECD countries. Applying a principal component analysis we distinguish between common factors and idiosyncratic components and determine whether non-stationarity stems from international or national stochastic trends. We find evidence that the common factors are I(1) while the idiosyncratic components are I(0). This finding indicates that cross-member cointegration exists and non-stationarity in exchange rates and fundamentals is mainly driven by common international trends. We find evidence that the common factors of the exchange rates and fundamentals are cointegrated. In addition, the estimated long-run coefficients of this common international relationship are in line with the suggestions of the monetary model with respect to income and money.     

What model for entry in first-price auctions? A nonparametric approach

We develop a selective entry model for first-price auctions that nests two polar models often estimated in the empirical literature on auctions, Levin and Smith (1994), and Samuelson (1985). The selective entry model features a pro-competitive selection effect. The selection effect is shown to be nonparametrically identifiable, and a nonparametric test for its presence is proposed. This test can be used to discriminate between the two polar models.     

How much should an investor trust the startup entrepreneur? A network model

Trust is an important determinant of start-up financing. In a simple agent-based model it is determined what the best trusting strategy is for a collective of investors and whether it is rational for an individual investor to deviate from this collective optimum. Trust depends on a measure of social distance and is the precondition for investment. Trust increases and decreases based on whether an investor is satisfied with the interest payments received from an entrepreneur. If an investor is dissatisfied, he terminates the relation with the entrepreneur. For assessing the quality of their own investments, investors communicate with other investors in a network-like structure. I find that, as a collective, it is best for investors to compare their returns critically in order to identify unproductive entrepreneurs, but to be tolerant regarding existing links to entrepreneurs in order not to terminate profitable relations because of minor productivity drops. However, it is optimal for an individual investor to deviate from this strategy and to be less easily disappointed, but to decrease trust in larger steps. In a sense, an individual investor can free ride on the others’ critical assessment. If all investors behave according to this latter strategy, too many unproductive firms remain in the market and the average investor’s return is lower than in the collective optimum.     

Deunionization and job polarization – a macroeconomic model analysis for a small open economy

Declining unionization rates and job polarization are two important labor market developments of recent decades. A large body of literature has analyzed these phenomena separately, but little has been done to see whether there is a link between them. We employ a macroeconomic model for a small open economy with a large input–output core to analyze how deunionization may cause job polarization. Our analysis shows that medium-skilled workers are negatively affected by deunionization, mainly as a result of the heterogeneity of the elasticities of substitution between different types of labor. While the elasticities of substitution between high- and medium-skilled labor are relatively low, the elasticities of substitution between medium- and low-skilled are relatively high. As a result, when deunionization leads to increased wage dispersion, we find that demand for low-skilled increases at the expense of medium-skilled labor, thus yielding a more polarized labor market.     

Toward the human – Centered approach. A revised model of individual acceptance of AI

The aim of the study is to understand how humans' acceptance of Artificial Intelligences (AIs) affects human resource management (HRM). To this end, we propose an original conceptual framework based on the idea of a sustainable growth driven by the interplay between AI and HRM. Current academic debate is overly concerned by the impact that future AI will have on business and society. One of the central aspects of the conversation is whether or not AI will replace humans in value-added activities. The study remarks that humanoids are an amplificator of human potential, in light of a human-centered approach. In this vein, present work reconceptualizes the tenets of society 5.0 by considering the category of “innovation ventura”, the evolution of the innovative enterprise in the next AI landscape.     

Validating an agent-based model of the Zipf׳s Law: A discrete Markov-chain approach

This study discusses the validation of an agent-based model of emergent city systems with heterogeneous agents. To this end, it proposes a simplified version of the original agent-based model and subjects it to mathematical analysis. The proposed model is transformed into an analytically tractable discrete Markov model, and its city size distribution is examined. Its discrete nature allows the Markov model to be used to validate the algorithms of computational agent-based models. We show that the Markov chains lead to a power-law distribution when the ranges of migration options are randomly distributed across the agent population. We also identify sufficient conditions under which the Markov chains produce the Zipf׳s Law, which has never been done within a discrete framework. The conditions under which our simplified model yields the Zipf׳s Law are in agreement with, and thus validate, the configurations of the original heterogeneous agent-based model.     

Type A behaviour at work – an empirical study of Taiwanese managers and entrepreneurs

Bortner's Type A Behaviour Questionnaires were used to explore the work behaviour of Chinese managers and entrepreneurs in Taiwan and to investigate how that behaviour was influenced by occupation, age and gender. One hundred and seventeen subjects participated in the study, of which 45 were also interviewed. The mean score on the questionnaire was 74.68, the median (74) and the mode (76) within a scoring range of 0–140. Eighty-four subjects registered scores of 80 or less (Type B behaviour) and 33 came within the mid-range of 81–120. None of the subjects registered scores of 121–40 (Type A behaviour). The highest score of 113 was registered by a female bank vice-president and the lowest (47) by a male manager working in a charitable organization and about to retire. The results are discussed within the context of Chinese cultural traditional and parenting practices, the unique characteristics of Taiwan's recent history and the subjects' career experience.     

Panel data and descriptor for energy econometrics – an efficiency,resilience and innovation analysis

Quality & Quantity - The work at hand presents a new extensive panel dataset for energy economics, econometrics and policy. The referred dataset is made of 5000 observations circa, including 6...     

Which model of technology transfer for nanotechnology? A comparison with biotech and microelectronics

Nanotechnologies are often presented as breakthrough innovations, where technology transfer and knowledge-bridging will play a pivotal role in the industrial dynamics. This article investigates the model of knowledge transfer in the nanotechnologies in depth, by comparing it with the models of two recently emerged technologies: biotech and microelectronics. Our results show that the nanotechnology transfer model is very different from that involved in biotechnology evolution: while small–medium firms play a valuable technology-bringing role, the central function of “translating” new knowledge between public research and industry is carried by the larger firms, just as it was in the early stages of the microelectronics sector. These results suggest that specific policy initiatives to facilitate biotech's transfer are inappropriate to boost the diffusion of nanotechnology.     

Innovation problems and search for solutions in crowdsourcing platforms – A simulation approach

Crowdsourcing initiatives are increasingly spreading among organisations aiming at outsourcing the development of solutions to internal innovation problems to external problem solvers. However, while knowledge about crowdsourcing is growing, a complete understanding of the underlying dynamics of these initiatives is still lacking. This study aims at elucidating this topic by investigating the influence exerted by the interplay between the characteristics of innovation problems, individuals developing solutions (problem solvers), and crowdsourcing platforms on the related problem solving performance. Specifically, we use NK fitness landscapes to simulate the search for solutions conducted by problem solvers in several scenarios, depending on the decomposability and accuracy of delineation of the innovation problems, the degree of bounded rationality of the solvers, and the cooperation policies of the crowdsourcing platforms. Our findings contribute to the development of the theory on search for solutions in crowdsourcing initiatives, by revealing the characteristics of problem solvers and the types of platforms that maximise the performance of the problem solving process, as the quality of the best solution provided and the time required to elaborate on it, according to specific innovation problems. Furthermore, our findings promote the formulation of guidelines for organisations using crowdsourcing to solve their innovation problems, and for the crowdsourcing platforms’ managers.     

Mapping potentials for input–output-based innovation flows in industrial clusters – an application to Germany

Our paper pursues two aims: first, it presents an approach based on input–output innovation flow matrices to study intersectoral innovation flows within industrial clusters. Second, we apply this approach to the identification of structural weaknesses in East Germany relative to the western part of the country. The case of East Germany forms an interesting subject because while its convergence process after unification began promisingly in the first half of the 1990s, convergence has since slowed down. The existing gap can now be traced mainly to structural weaknesses in the East German economy, such as the absence of strong industrial cluster structures. With this in mind, we investigate whether East Germany does in fact reveal the abovementioned structural weaknesses. Does East Germany possess fewer industrial clusters? Are they less connected? Does East Germany lack specific clusters that are also important for the non-clustered part of the economy?     

What is required for greener supplier selection? A literature review and conceptual model development

This paper examines the existing literature on green supplier selection. In total, 60 articles are reviewed, all published in peer-reviewed journals between 1991 and 2011. The articles are analyzed in terms of several general variables such as type of research and theoretical viewpoint, as well as more specific variables such as the supply chain position considered, stages of the supplier selection process studied, and the perspective taken on environmental criteria. The main findings are threefold. First, analytical research, focusing on developing normative decision models for the final stage in green supplier selection is clearly most dominant, employing a wide range of techniques. Second, empirical research is less prominent and generally lacks a clear theoretical background. Third, very little conceptual research has been done linking green supplier selection to an organization's strategy. Research on green supplier selection is highly fragmented and in danger of overemphasizing the technical aspects of supplier selection. Based on this review of the articles, a conceptual model of green supplier selection is presented, aimed at integrating the different dimensions of green supplier selection and identifying directions for future research.     

A new look at an old problem: A positive psychology lens on discrimination – identity builders and work-related outcomes

Although many scholars and practitioners continue to emphasize the benefits of a diverse workforce, discrimination remains an impediment to diversity and inclusion. For African Americans, who are uniquely stigmatized in the United States as descendants of enslaved people, merely having a “black name” or Afro-centric hairstyle can result in employment discrimination. Despite these outcomes, many African Americans remain resilient while facing discrimination. Utilizing positive organizational scholarship and the positive work-related identity typology as a framework, we propose a conceptual model that examines how African Americans' experiences enable them to shape a positive identity and serve as protective buffers against discrimination. Importantly, we suggest this identity process empowers African Americans to overcome discrimination, still perform well, and not voluntarily quit. We conclude with a discussion of our model's impact on African Americans and other stigmatized minorities and suggestions for future human resource management research and practice.