The amount of data in our world has been exploding, and analyzing large data sets—so-called big data— will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.

Big data: The next frontier for innovation, competition, and productivity

Companies have realized they need to hire data scientists, academic institutions are scrambling to put together data-science programs, and publications are touting data science as a hot-even "sexy"-career choice. However, there is confusion about what exactly data science is, and this confusion could lead to disillusionment as the concept diffuses into meaningless buzz. In this article, we argue that there are good reasons why it has been hard to pin down exactly what is data science. One reason is that data science is intricately intertwined with other important concepts also of growing importance, such as big data and data-driven decision making. Another reason is the natural tendency to associate what a practitioner does with the definition of the practitioner's field; this can result in overlooking the fundamentals of the field. We believe that trying to define the boundaries of data science precisely is not of the utmost importance. We can debate the boundaries of the field in an academic setting, but in order for data science to serve business effectively, it is important (i) to understand its relationships to other important related concepts, and (ii) to begin to identify the fundamental principles underlying data science. Once we embrace (ii), we can much better understand and explain exactly what data science has to offer. Furthermore, only once we embrace (ii) should we be comfortable calling it data science. In this article, we present a perspective that addresses all these concepts. We close by offering, as examples, a partial list of fundamental principles underlying data science.

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Data science and its relationship to big data and data-driven decision making

Research on the luminescent solar concentrator (LSC) over the past thirty-odd years is reviewed. The LSC is a simple device at its heart, employing a polymeric or glass waveguide and luminescent molecules to generate electricity from sunlight when attached to a photovoltaic cell. The LSC has the potential to find extended use in an area traditionally difficult for effective use of regular photovoltaic panels: the built environment. The LSC is a device very flexible in its design, with a variety of possible shapes and colors. The primary challenge faced by the devices is increasing their photon-to-electron conversion efficiencies. A number of laboratories are working to improve the efficiency and lifetime of the LSC device, with the ultimate goal of commercializing the devices within a few years. The topics covered here relate to the efforts for reducing losses in these devices. These include studies of novel luminophores, including organic fluorescent dyes, inorganic phosphors, and quantum dots. Ways to limit the surface and internal losses are also discussed, including using organic and inorganic-based selective mirrors which allow sunlight in but reflect luminophore-emitted light, plasmonic structures to enhance emissions, novel photovoltaics, alignment of the luminophores to manipulate the path of the emitted light, and patterning of the dye layer to improve emission efficiency. Finally, some possible ‘glimpses of the future’ are offered, with additional research paths that could result in a device that makes solar energy a ubiquitous part of the urban setting, finding use as sound barriers, bus-stop roofs, awnings, windows, paving, or siding tiles.

Thirty Years of Luminescent Solar Concentrator Research: Solar Energy for the Built Environment

The field of nanocrystal quantum dots (QDs) is already more than 30 years old, and yet continuing interest in these structures is driven by both the fascinating physics emerging from strong quantum confinement of electronic excitations, as well as a large number of prospective applications that could benefit from the tunable properties and amenability toward solution-based processing of these materials. The focus of this review is on recent advances in nanocrystal research related to applications of QD materials in lasing, light-emitting diodes (LEDs), and solar energy conversion. A specific underlying theme is innovative concepts for tuning the properties of QDs beyond what is possible via traditional size manipulation, particularly through heterostructuring. Examples of such advanced control of nanocrystal functionalities include the following: interface engineering for suppressing Auger recombination in the context of QD LEDs and lasers; Stokes-shift engineering for applications in large-area luminesce...

Spectroscopic and Device Aspects of Nanocrystal Quantum Dots

Big Data for Development: A Review of Promises and Challenges Martin Hilbert, University of California, Davis; hilbert@ucdavis.edu Author’s version Hilbert, M. (2016). Big Data for Development: A Review of Promises and Challenges. Development Policy Review, 34(1), 135–174. http://doi.org/10.1111/dpr.12142 Abstract The article uses a conceptual framework to review empirical evidence and some 180 articles related to the opportunities and threats of Big Data Analytics for international development. The advent of Big Data delivers the cost-effective prospect to improve decision-making in critical development areas such as health care, economic productivity, and security. At the same time, all the well-known caveats of the Big Data debate, such as privacy concerns and human resource scarcity, are aggravated in developing countries by long-standing structural shortages in the areas of infrastructure, economic resources, and institutions. The result is a new kind of digital divide: a divide in data-based knowledge to inform intelligent decision- making. The article systematically reviews several available policy options to foster the opportunities and minimize the risks. Keywords: Big Data, decision-making, innovation, ICT, digital divide, digital, international development. Acknowledgements: The author thanks International Development Research Centre Canada (IDRC) for commissioning a more extensive study that laid the groundwork for the present article. He is also indebted to Manuel Castells, Nathan Petrovay, Francois Bar, and Peter Monge for food for thought, and to Matthew Smith, Rohan Samarajiva, Sriganesh Lokanathan, and Fernando Perini for helpful comments on draft versions, and thanks the United Nations Economic Commission for Latin America and the Caribbean (UN-CEPAL), where part of the research was undertaken. The views expressed herein are those of the author and do not necessarily reflect the views of the United Nations.

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Big Data for Development: A Review of Promises and Challenges

We examine whether firms that emphasize decision making based on data and business analytics (“data driven decision making” or DDD) show higher performance. Using detailed survey data on the business practices and information technology investments of 179 large publicly traded firms, we find that firms that adopt DDD have output and productivity that is 5-6% higher than what would be expected given their other investments and information technology usage. Furthermore, the relationship between DDD and performance also appears in other performance measures such as asset utilization, return on equity and market value. Using instrumental variables methods, we find evidence that the effect of DDD on the productivity do not appear to be due to reverse causality. Our results provide some of the first large scale data on the direct connection between data-driven decision making and firm performance.

Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?

Luminescent solar concentrators (LSCs) use dye molecules embedded in a flat-plate waveguide to absorb solar radiation. Ideally, the dyes re-emit the absorbed light into waveguide modes that are coupled to solar cells. But some photons are always lost, re-emitted through the face of the LSC and coupled out of the waveguide. In this work, we improve the fundamental efficiency limit of an LSC by controlling the orientation of dye molecules using a liquid crystalline host. First, we present a theoretical model for the waveguide trapping efficiency as a function of dipole orientation. Next, we demonstrate an increase in the trapping efficiency from 66% for LSCs with no dye alignment to 81% for a LSC with vertical dye alignment. Finally, we show that the enhanced trapping efficiency is preserved for geometric gains up to 30, and demonstrate that an external diffuser can alleviate weak absorption in LSCs with vertically-aligned dyes.

Dye alignment in luminescent solar concentrators: I. Vertical alignment for improved waveguide coupling

We describe Linearly Polarized Luminescent Solar Concentrators (LP-LSCs) to replace conventional, purely absorptive, linear polarizers in energy harvesting applications. As a proof of concept, we align 3-(2-Benzothiazolyl)-N,N-diethylumbelliferylamine (Coumarin 6) and 4-dicyanomethyl-6-dimethylaminostiryl-4H-pyran (DCM) dye molecules linearly in the plane of the substrate using a polymerizable liquid crystal host. We show that up to 38% of the photons polarized on the long axis of the dye molecules can be coupled to the edge of the device for an LP-LSC based on Coumarin 6 with an order parameter of 0.52.

Dye alignment in luminescent solar concentrators: II. Horizontal alignment for energy harvesting in linear polarizers

Wages are an important factor that affects firm performance by influencing both the composition of the workforce and the behaviors of the employees. This study investigates how seniority-based pay affects firm performance. Using the Human Capital Corporate Panel (HCCP), we found that sales per employee, but not return on assets, was positively associated with the extent to which wages were increased by tenure. Limited support was found for the moderating effect of technological changes. These results demonstrate the importance of pay structures with regard to firm performance. 

Heekyung Kim

Papers

Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?

Dye alignment in luminescent solar concentrators: I. Vertical alignment for improved waveguide coupling

Dye alignment in luminescent solar concentrators: II. Horizontal alignment for energy harvesting in linear polarizers

The Effect of Seniority-based Pay on Firm Performance