Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.     

Setting Risk‐Informed Environmental Standards for Bacillus Anthracis Spores

In many cases, human health risk from biological agents is associated with aerosol exposures. Because air concentrations decline rapidly after a release, it may be necessary to use concentrations found in other environmental media to infer future or past aerosol exposures. This article presents an approach for linking environmental concentrations of Bacillus. anthracis (B. anthracis) spores on walls, floors, ventilation system filters, and in human nasal passages with human health risk from exposure to B. anthracis spores. This approach is then used to calculate example values of risk‐informed concentration standards for both retrospective risk mitigation (e.g., prophylactic antibiotics) and prospective risk mitigation (e.g., environmental clean up and reoccupancy). A large number of assumptions are required to calculate these values, and the resulting values have large uncertainties associated with them. The values calculated here suggest that documenting compliance with risks in the range of 10^?4 to 10^?6 would be challenging for small diameter (respirable) spore particles. For less stringent risk targets and for releases of larger diameter particles (which are less respirable and hence less hazardous), environmental sampling would be more promising.     

The Influence of Human Factors and Specialist Involvement on Information Systems Success

Despite remarkable advances in informationtechnology (IT), many computer-based information systems(IS) still fall short of performance expectations. Agrowing share of these implementation failures are due to nontechnical factors. This articleconsiders the human factors and human resource (HR)management issues associated with IT assimilation. Ataxonomy of specialist roles in the IS adoption process is proposed and illustrated in a series ofbrief case studies. The results from a fieldinvestigation are then reported. The relationshipsbetween different HR specialist roles and selected ISsuccess measures were examined in more than 60 organizationsacross East and Southeast Asia. Proactive and supportiveHR roles were found to be associated with greater usersatisfaction, smoother organizational change and improved productivity, but did notsignificantly affect perceived output quality. Theimplications for management practice are discussed andspecific areas for further research areidentified.     

A Qualitative Assessment of South African Adolescents' Motivations For and Against Substance Use and Sexual Behavior

Focus groups (N=15 groups; 8 with girls, 7 with boys) with adolescents in high schools near Cape Town, South Africa, were used to conduct a qualitative investigation of reported reasons for using and not using substances and for having and not having sex. Adolescents reported Enhancement, Negative States, Social, and Aversive Social motivations for both substance use and sexual behavior. In addition, being addicted as a reason for using drugs and rape as a context for sexual behavior were frequently reported. Motivations against behaviors included Physical/Behavioral Consequences, Ethical Objections, Social Disapproval, and Incompatible Activities and Goals reasons. Preventive interventions should address existing motivations for and against substance use and sexual behavior to acknowledge adolescents' experiences in context.     

The Optimal Degree of Discretion in Monetary Policy

How much discretion should the monetary authority have in setting its policy? This question is analyzed in an economy with an agreed‐upon social welfare function that depends on the economy's randomly fluctuating state. The monetary authority has private information about that state. Well designed rules trade off society's desire to give the monetary authority discretion to react to its private information against society's need to prevent that authority from giving in to the temptation to stimulate the economy with unexpected inflation, the time inconsistency problem. Although this dynamic mechanism design problem seems complex, its solution is simple: legislate an inflation cap. The optimal degree of monetary policy discretion turns out to shrink as the severity of the time inconsistency problem increases relative to the importance of private information. In an economy with a severe time inconsistency problem and unimportant private information, the optimal degree of discretion is none.     

INCOMPLETE SOCIAL CONTRACTS

There is a long normative ‘Social Contract’ tradition that attempts to characterize ex‐post income inequalities that are agreeable to all ‘behind a veil of ignorance.’ This paper takes a similar normative approach to characterize social decision‐making procedures. It is shown that quite generally some form of majority‐voting is preferred to unanimity ‘behind a veil of ignorance’ whenever society faces deadweight costs in making compensating transfers. Deviations from unanimity (or ex‐post Pareto optimality) are ex‐ante efficient to the extent that they economize on costly compensating transfers. Put another way, the optimal decision rule trades off the benefits of minority protection and those from greater flexibility. (JEL: H11, G33, G34, D63, P16, P48)     

Chance Constrained Programming Approach to Empirical Analyses of Mutual Fund Investment Strategies*

Chance constrained programming concepts are used to formalize risk and return relations which are then modeled for use in an empirical study of mutual fund behavior during the period 1984 through 1988. The publicly announced strategies of individual funds are used to form ex ante risk classifications which are employed in examining ex post performance. Negative relations between risk and return held in every year of the period studied. The bearing of these negative risk-return findings for the Bowman paradox, as studied in the strategic management literature, are thus extended from the industrial firms studied by Bowman (and others) and shown to be present even in these investment oriented mutual funds in each of the years of the great bull market from 1984 through 1988. Finally, our use of chance constrained programming enables us to separate risk from return behavior and evaluate their relative strengths as sources of these negative relations, which are found to be more in the returns than the risks.