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Book part
Publication date: 26 October 2020

Gregg M. Gascon and Gregory I. Sawchyn

Bundled payments for care are an efficient mechanism to align payer, provider, and patient incentives in the provision of health care services for an episode of care. In…

Abstract

Bundled payments for care are an efficient mechanism to align payer, provider, and patient incentives in the provision of health care services for an episode of care. In this chapter, we use agency theory to examine the evolution of bundled payment programs in private and public payer arrangements, and postulate future directions for bundled payment development as a key component in the provision and payment of health care services.

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Integrated Land-Use and Transportation Models
Type: Book
ISBN: 978-0-080-44669-1

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Book part
Publication date: 4 March 2015

Rajmund Mirdala

Deficits in fiscal and current account balances in a large number of countries reveal interesting implications of the causal relationship between internal and external…

Abstract

Deficits in fiscal and current account balances in a large number of countries reveal interesting implications of the causal relationship between internal and external imbalances. Empirical evidence about the occurrence of so-called twin deficits or twin surpluses provides crucial information about the validity of an intertemporal approach. However, most recent dynamic cyclical changes during the crisis period revealed many questions about the direct interconnection between macroeconomic performance and twin imbalances. In the paper we observe substantial features of twin imbalances in European transition economies. Event study (identification of large fiscal and current account changes and their parallel occurrence) and vector auto-regression methods will be employed to examine key aspects of twin imbalances. Our results suggest that current account deteriorations were predominately associated with negative public investment and savings balances (fiscal deficits), while current account improvements were predominately associated with positive private investment and savings balances, confirming empirical evidence about twin deficits in European transition economies.

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Book part
Publication date: 26 August 2010

Sergio Biggemann

Relationships are socially constructed by companies in interaction. This study explains the dynamic character of business-to-business relationships with the aid of rules…

Abstract

Relationships are socially constructed by companies in interaction. This study explains the dynamic character of business-to-business relationships with the aid of rules theory, a theory borrowed from the communications field. Two forms of rules are identified: constitutive rules guide the interpretation of the other's acts, and regulative rules guide the appropriate response to the interpreted act. Rules theory asserts that companies act as if applying these rules. Relationships provide not only the context in which the parties’ acts are performed but are also the result of such acts. Thus, relationships are potentially reshaped each time one party performs an act and the other party gives meaning to that act and reacts.

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Organizational Culture, Business-to-Business Relationships, and Interfirm Networks
Type: Book
ISBN: 978-0-85724-306-5

Abstract

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Integrated Land-Use and Transportation Models
Type: Book
ISBN: 978-0-080-44669-1

Abstract

Many jurisdictions fine illegal cartels using penalty guidelines that presume an arbitrary 10% overcharge. This article surveys more than 700 published economic studies and judicial decisions that contain 2,041 quantitative estimates of overcharges of hard-core cartels. The primary findings are: (1) the median average long-run overcharge for all types of cartels over all time periods is 23.0%; (2) the mean average is at least 49%; (3) overcharges reached their zenith in 1891–1945 and have trended downward ever since; (4) 6% of the cartel episodes are zero; (5) median overcharges of international-membership cartels are 38% higher than those of domestic cartels; (6) convicted cartels are on average 19% more effective at raising prices as unpunished cartels; (7) bid-rigging conduct displays 25% lower markups than price-fixing cartels; (8) contemporary cartels targeted by class actions have higher overcharges; and (9) when cartels operate at peak effectiveness, price changes are 60–80% higher than the whole episode. Historical penalty guidelines aimed at optimally deterring cartels are likely to be too low.

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The Law and Economics of Class Actions
Type: Book
ISBN: 978-1-78350-951-5

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Article
Publication date: 14 May 2018

Rogelio V. Mercado Jr

The purpose of this paper is to consider the transition of surge episodes to stop episodes and differentiates between two types of surges, namely, surges that end in stops…

Abstract

Purpose

The purpose of this paper is to consider the transition of surge episodes to stop episodes and differentiates between two types of surges, namely, surges that end in stops and surges that end in normal episodes.

Design/methodology/approach

Previous studies show that surges end in output contractions, crises, and reversals of capital inflows. However, when one looks closely at the data, more than half of surges end in normal episodes at least four quarters following the last surge quarter.

Findings

The results show the varying significance of global and domestic factors correlated with the occurrence of surges leading to stops and the size of gross inflows during these two types of surges.

Originality/value

The findings highlight the importance of differentiating between these two types of surges as it leaves scope for policy design in safeguarding financial stability amidst surging capital inflows.

Details

Journal of Economic Studies, vol. 45 no. 2
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 28 October 2014

Priyanka Chaurasia, Sally McClean, Chris D. Nugent and Bryan Scotney

The purpose of this paper is to discuss an online sensor-based support system which the authors believe can be useful in such scenarios. Persons with a cognitive…

Abstract

Purpose

The purpose of this paper is to discuss an online sensor-based support system which the authors believe can be useful in such scenarios. Persons with a cognitive impairment, such as those with Alzheimer’s disease, suffer from deficiencies in cognitive skills which reduce their independence; such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (IADLs).

Design/methodology/approach

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and on-going IADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the IADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability taken into consideration the IADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the IADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity, thus updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

Findings

The results of this study verify that by including duration information the prediction accuracy of the model is increased and the confidence level for the next step in the IADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single sensor activation in comparison to an alternative approach which did not consider activity durations.

Practical implications

Duration information to a certain extent has been widely ignored by activity recognition researchers and has received a very limited application within smart environments.

Originality/value

This study concludes that incorporating progressive duration information into partially observed sensor sequences of IADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

Details

International Journal of Pervasive Computing and Communications, vol. 10 no. 4
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 26 August 2014

Priyanka Chaurasia, Sally McClean, Chris D. Nugent and Bryan Scotney

This paper aims to discuss an online sensor-based support system which is believed to be useful for persons with a cognitive impairment, such as those with Alzheimer’s…

Abstract

Purpose

This paper aims to discuss an online sensor-based support system which is believed to be useful for persons with a cognitive impairment, such as those with Alzheimer’s disease, suffering from deficiencies in cognitive skills which reduce their independence. Such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (iADLs).

Design/methodology/approach

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and ongoing iADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the iADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability, taking into consideration the iADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the iADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity; thus, updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

Findings

The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the iADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single-sensor activation in comparison to an alternative approach which did not consider activity durations. Thus, it is concluded that incorporating progressive duration information into partially observed sensor sequences of iADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

Originality/value

Activity duration information can be a potential feature in measuring the performance of a user and distinguishing different activities. The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the activity is also increased. The use of duration information in online prediction of activities can also be associated to monitoring the deterioration in cognitive abilities and in making a decision about the level of assistance required. Such improvements have significance in building more accurate reminder systems that precisely predict activities and assist its users, thus, improving the overall support provided for living independently.

Details

International Journal of Pervasive Computing and Communications, vol. 10 no. 3
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 1 January 2002

Paul J. Taylor

This paper examines whether patterns in communication behavior over time can predict the outcome of crisis negotiations. A sample of 189 interaction episodes was…

Abstract

This paper examines whether patterns in communication behavior over time can predict the outcome of crisis negotiations. A sample of 189 interaction episodes was transcribed from 9 resolved negotiations and coded according to differences in the degree and type of behavior. Partial order scalogram analysis (POSAC) was used to produce a graphical representation of the similarities and differences among episodes while simultaneously uncovering the role of each behavior in shaping the negotiation process. Results showed that episodes could be represented along a partially ordered scale of competitiveness, which was structured by the occurrence of two types of behavior: Distributive‐Expressive and Integrative‐Instrumental. The likelihood of negotiation success reduced with movement up the competitive scale, and negotiations involving episodes that passed a threshold of extreme competition on the scale inevitably ended unsuccessfully regardless of future developments. As negotiations developed over time, behavior alternated between periods of increasing cooperation and periods of increasing competition, with unsuccessful negotiations associated with a concluding trend of increasing competitive behavior.

Details

International Journal of Conflict Management, vol. 13 no. 1
Type: Research Article
ISSN: 1044-4068

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