The Endogenous Sequential Probit model: An application to the demand for hospital utilization

This paper develops the Endogenous Sequential Probit model to analyze the effect of managed care on hospital utilization by adult married US population and finds that managed care gives disincentives to utilize hospital care relative to the standard indemnity plans.     

The <Emphasis Type="Italic">n</Emphasis>-person Kalai-Smorodinsky bargaining solution under pre-donations

This study examines the behavior of simple n-person bargaining problems under pre-donations where the Kalai-Smorodinsky (KS) solution is operant. Pre- donations are a unilateral commitment to transfer a portion of one’s utility to someone else, and are used to distort the bargaining set and thereby influence the bargaining solution. In equilibrium, these pre-donations are Pareto-improving over the undistorted solution; moreover, when the agents’ preferences are sufficiently distinct, the equilibrium solution coincides with the concessionary division rule.     

Labor market outcomes,savings accumulation,and return migration

In this paper, I examine the determinants of return migration from Germany for immigrants from four different source countries, and test the savings accumulation conjecture that is used to rationalize return migration decisions using both cross-country and time variation in purchasing power parity. The empirical results confirm the savings accumulation conjecture. Therefore, return migration can be seen as part of optimal life-cycle location choices in this context. I also examine how labor market outcomes influence return decisions. A key finding here is that unlike previous studies, which find a positive impact of unemployment on return migration, I find that the direction of the impact of unemployment changes by the spell length.     

THE PROFITABILITY OF COLONIAL INVESTMENT

This paper develops a model for studying colonial investment in which the metropolitan government restricts the amount of investment in the colony in order to maximize the net profits earned in the colony. The model explicitly includes the threat of subversive activity by the indigenous colonial population. The analysis suggests why historically some countries but not others became colonies and why many colonies that were initially profitable subsequently become unprofitable and were abandoned. The model also has implications for the amount of investment in colonies, the allocation of indigenous colonial labor between production and subversive activity, and the distribution of income between colonial firms and the indigenous population.     

Strategic consensus mapping: A new method for testing and visualizing strategic consensus within and between teams

Research on strategic consensus focuses primarily on the extent of agreement among team members regarding organizational strategy. It does not include elements such as the content of the agreement, between‐group consensus, or the significance of differences in consensus (e.g., for evaluating the effectiveness of strategic interventions). We propose a new analytical approach, Strategic Consensus Mapping, that provides a comprehensive analysis of strategic consensus within and between groups and that includes intuitive and easy‐to‐understand visualizations. This approach offers researchers the necessary tools for integrative theory building in strategic consensus, as well as in the broader managerial and organizational cognition domain. Using a case example, we illustrate the proposed methods for a multidimensional, multilevel, and longitudinal analysis of strategic consensus. Copyright © 2013 John Wiley & Sons, Ltd.     

Determining the causal relationship among the research streams of the operations management course

Due to the rapid changes in technology, there have been dramatic changes in manufacturing systems and techniques in almost all industries. In this sense, higher education institutions have become more important as they play a key role in ensuring the labor force in the industry. In the present study, the research streams for operations management course were established, then fuzzy total interpretive structural modelling technique was employed to analyze the causal relations and influences among the factors. The purpose of the study was to determine the relationships among the research streams of operations management course.     

Learning strategic cooperative behavior in industrial symbiosis: A game‐theoretic approach integrated with agent‐based simulation

This paper investigates the negotiation phase of industrial symbiosis relationships, where companies exchanging wastes for inputs need to develop strategies on how to share the additional costs to operate the industrial symbiosis business. The business behavior is approached as a “coopetition” problem where companies need to cooperate to reduce waste discharge costs and traditional input purchase costs and dive into competition to pay a minimum share of additional costs (i.e., waste treatment, waste transportation, and transaction costs) of operating industrial symbiosis. A noncooperative game‐theoretical model for sharing the additional costs is proposed that highlights the two strategies that companies can adopt aimed at sharing costs: a fair strategy and an opportunistic strategy. Then, an agent‐based model is used to simulate the game iterated over time and investigate how the players can adapt their strategies according to their past experience. Simulation results show that players learn that playing the fair strategy is beneficial in the long period, despite in the short period they can gain more benefit by playing the opportunistic strategy. Findings of the paper are critically important to reduce the business and managerial barriers against the formation of industrial symbiosis networks and to stimulate innovative thinking of company managers to foster the development of the circular economy. The paper proposes theoretical, managerial, and policy implications, which are discussed in detail in a comparative manner between linear and circular economy.     

Counting the uncounted: The consequences of children's domestic chores for health and education in Ethiopia

Much of the existing literature on the economics of child labor assumes that child labor is synonymous with employment in income‐generating activities. However, children also perform domestic chores, and excessive involvement in chores may be detrimental to their wellbeing. This paper investigates the effect on child health and education outcomes of participation in domestic chores as well as participation in income‐generating activities. Our data come from the 2014 Young Lives survey of Ethiopia. We use the guidelines of the 18th International Conference of Labor Statisticians and the United Nations Children's Fund to make a distinction between light work and harmful work, and apply this distinction to both domestic chores and income‐generating work. Using an instrumental variables approach, we find that involvement in harmful domestic chores is strongly associated with poor health and education outcomes. Our findings suggest that excessive involvement in domestic chores constitutes a form of child labor. Ignoring domestic chores will lead to an underestimate of the prevalence of child labor, especially among girls, whose exposure to chores is much higher, on average, than that of boys.     

Using long short‐term memory neural networks to analyze SEC 13D filings: A recipe for human and machine interaction

We implement an efficient methodology for extracting themes from Securities Exchange Commission 13D filings using aspects of human‐assisted active learning and long short‐term memory (LSTM) neural networks. Sentences from the ‘Purpose of Transaction’ section of each filing are extracted and a randomly chosen subset is labelled based on six filing themes that the existing literature on shareholder activism has shown to have an impact on stock returns. We find that an LSTM neural network that accepts sentences as input performs significantly better, with precision of 77%, than an alternately specified neural network that uses the common bag of words approach. This indicates that both sentence structure and vocabulary are important in classifying SEC 13D filings. Our study has important implications, as it addresses the recent cautions raised in the literature that analysis of finance and accounting‐related text sources should move beyond bag‐of‐words approaches to alternatives that incorporate the analysis of word sense and meaning reflecting context.