Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

Balancing social and political strategies in emerging markets: Evidence from India

This article explores the substitution and complementary effects between political and social strategies on firm performance in the context of an emerging market (EM). Using in‐depth, historical case‐study approach, the article investigates how companies integrate political and social resources in this market. Corporate performance includes traditional measures, such as accounting performance and nonfinancial measures like the ease of doing business. The study finds that social strategies are stronger enablers of firm long‐term performance than political strategies. The latter have a short‐term impact on performance, but their success over time is limited. The main drawback of reliance on political resources in EMs is the lack of political stability, fragmented polity, and weak political coalitions. We identify rather limited evidence of firms using these two strategies as complements. Thus, we suggest that firms should employ both these strategies in the EM.     

Part–Time Work During Post–Compulsory Education And Examination Performance: Help Or Hindrance?

This paper examines the effects on examination performance of having a part–time job whilst in full–time post–sixteen education, using new data on young people in Northern Ireland. Around 35% engaged in part time employment during their education spell, compared to over 60% found by recent GB studies. This may be related to Northern Ireland's comparatively slack youth labour market and might reflect part–time employment levels in other peripheral regions. Our estimations suggest working part–time per se is not detrimental to examination performance, although working long hours is. Policy makers might improve educational performance by reducing incentives to work long hours.     

Noise Trading and the Management of Operational Risk; Firms,Traders and Irrationality in Financial Markets*

abstract Efficient market models cannot explain the high level of trading in financial markets in terms of asset portfolio adjustment. It is presumed that much of this excessive trading is irrational ‘noise’ trading. A corollary is that there must either be irrational traders in the market or rational traders with irrational aberrations. The paper reviews the various attempts to explain noise trading in the finance literature, concluding that the persistence of irrationality is not well explained. Data from a study of 118 traders in four large investment banks are presented to advance reasons why traders might seek to trade more frequently than financial models predict. The argument is advanced that trades do not simply occur in order to generate profit, but it does not follow that such trading is irrational. Trading may generate information, accelerate learning, create commitments and enhance social capital, all of which sustain traders' long term survival in the market. The paper treats noise trading as a form of operational risk facing firms operating in financial markets and discusses approaches to the management of such risk.     

Behavioural Microsimulation with Labour Supply Responses

This paper provides a technical survey of recent developments in behavioural microsimulation. We discuss the criteria by which models of labour supply may be chosen for application to behavioural microsimulation, and consider how such models may be augmented to control for fixed costs, child–related work costs, preference heterogeneity and endogeneity in wages. We describe methods by which non–linear budget constraints may be accommodated in estimation, policy simulations and welfare analysis, and discuss how stochastic terms may be factored into the simulation of behavioural responses to a policy shock.     

Life histories in housing research: the case of Pakistanis in Glasgow

The discussion centers on three key criticisms of life history techniques, which are reviewed and evaluated with reference to data from research on Pakistani housing histories in Glasgow. Firstly, the problem of bias is reframed as an issue of reflexivity, which enhances research findings. Secondly, awareness of the cultural construction of life histories allows greater depth of analysis. And thirdly the problem of the relationship between the life history and wider social forces is argued to increase awareness and understanding of social actor agency. In conclusion, we argue that life history techniques can develop research on housing careers, particularly of Pakistanis, provided certain of their properties are recognised in the process of analysis.     

Testing Alternative Regression Frameworks for Predictive Modeling of Health Care Costs

Predictive models of health care costs have become mainstream in much health care actuarial work. The Affordable Care Act requires the use of predictive modeling-based risk-adjuster models to transfer revenue between different health exchange participants. Although the predictive accuracy of these models has been investigated in a number of studies, the accuracy and use of models for applications other than risk adjustment have not been the subject of much investigation. We investigate predictive modeling of future health care costs using several statistical techniques. Our analysis was performed based on a dataset of 30,000 insureds containing claims information from two contiguous years. The dataset contains more than 100 covariates for each insured, including detailed breakdown of past costs and causes encoded via coexisting condition flags. We discuss statistical models for the relationship between next-year costs and medical and cost information to predict the mean and quantiles of future cost, ranking risks and identifying most predictive covariates. A comparison of multiple models is presented, including (in addition to the traditional linear regression model underlying risk adjusters) Lasso GLM, multivariate adaptive regression splines, random forests, decision trees, and boosted trees. A detailed performance analysis shows that the traditional regression approach does not perform well and that more accurate models are possible.     

Personal income tax mimicry: evidence from international panel data

This paper investigates personal income tax (PIT) mimicry at the international level. It is the first to empirically investigate the extent to which PIT mimicry varies along the tax schedule and the first to include nations which are not part of the OECD. We use data on international personal income tax schedules from the world tax indicators to estimate marginal and average tax rates at various multiples of per capita gross domestic product (GDP). These tax rates are then used to estimate the extent to which countries respond to their neighbors’ PIT policy. We find evidence of PIT mimicry using a balanced panel of 53 countries over 24 years. This finding is strongest for tax rates at lower multiples of per capita GDP and survives several robustness checks.