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Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing demand visibility, or ascertaining sustainable supplier practices. Managers in the traceability initiatives developing such technologies face a difficult question: which companies should they target as early adopters to ensure that their technology is broadly employed? To answer this question, managers must consider that supply chains are interlinked in complex networks and that a supply chain effect is inherent to traceability technologies. More specifically, the benefits obtained from traceability are conditional on technology adoption throughout a product's supply chain. We introduce a model of the dynamics of traceability technology adoption in supply chain networks to tackle the problem of selecting the smallest set of early adopters guaranteeing broad dissemination. Our model builds on extant diffusion models while incorporating that a firm's adoption decision depends on previous adoption decisions throughout its supply chains. We show that the problem is NP-hard and that no approximation within a polylogarithmic factor can be guaranteed for any polynomial-time algorithm. Nevertheless, we introduce an algorithm that identifies an exact solution in polynomial time under certain assumptions on the network structure and provide evidence that it is tractable for real-world supply chain networks. We further propose a random generative model that outputs networks consistent with real-world supply chain networks. The networks obtained display, whp, structures that allow us to find the optimal seed set in subexponential time using our algorithm. Our generative model also provides approximate seed sets when information on the network is limited.

We use a multivariate synthetic control method that matches the price and output dynamics jointly to evaluate the effects of the inflation targeting regime (IT) on the inflation and output growth of its early adopters (the ITers) – New Zealand, Canada, the United Kingdom, Sweden, and Australia. Once accounting for the inflation-output trade-off in the conduct of monetary policy, the ITers enjoyed lower inflation and/or higher output growth than their counterfactuals. These performances were economically important to justify IT central banks’ optimism with IT, both case-by-case and on average.

We show that change in Grayscale Bitcoin Trust premium is the single most significant predictor of Bitcoin daily return. This sentiment measure is similar to the closed-end fund discount measure as in Baker and Wurgler (2006), but more likely to reflect the excess demand from traditional investors than from blockchain specialists. Although there is a substantial variation in Bitcoin price quotes worldwide, this Grayscale premium and discount predict Bitcoin daily return for the most liquid Bitcoin exchanges. Using K-means clustering and LDA analysis, we find that this predictability is especially significant when there is a large variation in bullish and bearish market sentiment, innovation regarding CBDC, regulations on crypto exchanges, but not when there is innovation regarding blockchain technology or bitcoin mining. A simple long and short strategy based on this signal generates a daily alpha of 40 bps. These findings suggest that Bitcoin prices react with a delay to the information contained in the sentiment of traditional investors and investors who are constrained from directly holding Bitcoin.

This study aims to identify the factors that influence the adoption of smart contracts in the UK construction sector. A deductive questionnaire-based approach informed by the technology- organisation-environment (TOE) model is adopted. The framework is comprised of twelve independent variables and one dependent variable of smart contracts use intention. Ten hypotheses are developed to statistically test the causal relationships between the eleven variables of the research model. The study adopts a convenience sampling approach, with the population of interest being primarily drawn from among UK construction practitioners. The results generated from linear regression analysis suggest that the following four factors have a significant influence on the adoption of smart contracts: supply chain pressure, competitive pressure, top management support, and observability. The descriptive statistics obtained also offer a greater understanding of the perceptions and attitudes towards smart contracts across the UK construction sector. The results demonstrate the usefulness of a perception-based model that utilises the TOE framework to assess facets that influence the adoption of smart contracts. The study contributes to innovation diffusion studies in construction project management and supports “early adopters” at the footfall of the technology’s diffusion curve.

Recent technological advances have created unprecedented opportunities for consumer technology products to assume a new role, that of representing users’ social status. We study how social-reference-group effects impact firms’ product pricing, design, and targeting strategies. We find that, in a commonly-adopted strategy, Sequential Adoption, where early adopters (leaders) upgrade to a new version when new customers (followers) arrive and adopt the original version, a firm could benefit by leveraging a push effect on leaders who desire to escape from using the same version as followers. However, a strong reference-group effect can also hurt the firm due to a pull effect from the new version on followers who desire to assimilate with leaders. We then study how the firm should differentiate its product versions in two dimensions, functionality and exterior appearance, by leveraging the reference-group effect. We identify three optimal design policies: Functional-Only Differentiation, Joint Differentiation, and Exterior-Focused Differentiation, which differ in the firm’s focus on the two design dimensions. Two factors, the strength of the reference-group effect and the base functional value of the product, jointly determine the conditions under which each design policy dominates the others.

This paper studies the impact of consumers' social learning from the reviews of early adopters of a new product. We consider a two-period setting with an introduction (penetration) period followed by the product maturing period. Early buyers make purchase decisions in the introduction period under significant product valuation uncertainty and future price uncertainty and would like post reviews online to share their experiences about the product. The online product reviews posted by early adopters play an important role in shaping following consumers' product valuations and further influence their purchasing decisions. While the majority of research on social learning focuses on the impact of social learning on the consumer decisions and firm pricing in the maturing period, we find an indirect impact of electronic word-of-mouth (EWOM) on the strategic early buyers' purchase decisions and firm pricing in the introduction period. When early buyers make purchase decisions, they need to forecast the future second period price, estimate the expected utility from waiting, and compare it with the expected utility from buying early. We find that social learning increases the uncertainty in future price, which depends on reviews and therefore unknown, for early buyers in the introduction period. This price-uncertainty-increasing effect may balk early buyers from adopting in the introduction period and thus impact a firm's profit. Driven by this effect, we find that under social learning negative reviews may benefit a firm while positive reviews can also hurt a firm.

Who uses mobile money, and what do people do with it? This paper describes mobile money adoption patterns following the experimental introduction of mobile money for the first time in rural areas of Southern Mozambique. We use administrative and household survey data to characterize adopters as well as their mobile money usage patterns over three years. Adopters of mobile money (and early adopters in particular) are more educated than nonadopters, and they are also more likely to already hold a bank account. Positive self-selection of adopters should be considered when introducing mobile money as a tool for rapid financial inclusion.

California has been one of the early adopters of new energy storage technologies within the United States. The state has used multiple policy initiatives such as deployment targets, financial incentives, and market mechanism to facilitate such a market development. This motivates us to try to understand the various business models in the state and the minimum set of barriers that must be overcome for its successful deployment (and thereby development of the market). In our study, the former is achieved by assessing the various projects in the state, and the latter by creating a barrier-solution framework and verifying it by identifying the role of various policies/drivers in supporting various business models within California. We find that there are predominantly three business models in California: one for each Front-of-the-Meter, Behind-the-Meter, and Aggregated Behind-the-meter. We also find that at least one barrier from barrier categories associated with market demand and project economics along with all the barriers related to interconnection and market participation must be addressed for successful deployment of energy storage. Additionally, we recommend policy makers seeking to develop an energy storage market to start with developing Behind-the-meter market as it requires the least amount of intervention and then move to developing Front-of-the-meter market, and finally to aggregation of Behind-the-meter market.

This paper measures the effects of automated mortgage underwriting systems on leverage and house prices during the 1990s. In addition to reducing processing times, these systems expanded credit access by incorporating new rules informed by statistical analysis. In particular, Freddie Mac’s underwriting system, Loan Prospector, applied a proprietary set of rules which allowed lenders to approve loans with high debt-to-income ratios. I obtain a list of lenders who were using Loan Prospector shortly after its release in 1995, and use variation in the market share of these lenders to study the effect on house prices. I show that early adopters of Loan Prospector expanded high leverage lending, and that counties exposed to these lenders experienced substantial relative growth in house prices starting in 1995. Based on my estimates, I argue that gradual adoption of the GSEs’ underwriting systems can explain a substantial share of U.S. house price growth during the late 1990s.

Since the early 1990s, when digitalisation began to open new opportunities for disseminating information, many academic journals started to introduce online services. However, while some studies suggest that online availability and free access to journal articles are positively connected to the number of citations an article receives, little is known about whether being an early adopter of digital services provides journals with a (long-term) competitive advantage in times of digital change. We use data from SSCI-listed management journals to examine which journals pioneered the introduction of digital services, to what extent first-mover advantages can be identified, and which journal characteristics are associated with citation-based performance indicators. Our results show that lower ranked journals were the first to introduce digital services and were beneficiaries of the digital age. Furthermore, we find a negative correlation between general submission fees and journal performance and that the top-performing journals of our sample are those of non-commercial publishers. Our analysis of the relationship between journal performance and the provision of open access contradicts previous studies, as we find no positive correlations between performance and open access on the journal level., Finanziert über die DEAL-Vereinbarung mit Wiley 2019-2022.

Untapped improvements in energy efficiency in the residential sector may deliver large savings in energy use and the CO2 associated emissions. Yet empirical assessments have been difficult and controversial. We collect monthly natural gas meter readings from a sample of homes in Transcarpathia, in Western Ukraine, an early adopter of the country’s trend away from district heating, from January 2013 to April 2017, a period over which the residential natural gas tariffs rose by over 700%. We combine the monthly meter readings with documentation about each household’s heating-related energy efficiency upgrades to the home (wall, attic or basement insulation; new windows; boiler replacement, and insulation around pipes) to form a panel dataset. We estimate the effect of the energy efficiency renovations on natural gas consumption, controlling for weather, income and government energy assistance. The decision to do the renovations and natural gas consumption are likely endogenous (people do the renovations because they hope to consume less), so we instrument for the renovations by creating a cross-validation instrument based on a supply-side argument. Even for a given type of energy efficiency upgrades, the estimated effect of the renovations varies dramatically in magnitude, depending on whether the renovations are instrumented for and on how detailed the fixed effects are. The coefficients on the renovations are almost always negative in our regressions, but practically and statistically significant only when we instrument for the renovations. This is in agreement with our respondents’ difficulty assessing whether the renovations had saved them gas or money. The IV estimates indicate that insulation delivers 13-24% reductions in natural gas usage, and up to a 5% internal rate of return (IRR) to the investment over 20 years. Judicious use of an existing government program can yield positive IRRs and make energy efficiency upgrades a good investment in a generally poor-performing housing market.

Management in America has become significantly more data-intensive, yet the economic, organizational, and strategic implications of this shift are poorly understood. Working with the U.S. Census Bureau, we developed measures of how manufacturing firms have used data to guide decision making over the past decade. In our large and representative sample, data-driven decision making (DDD) is strongly associated with increased productivity. The benefits attributable to DDD are distinct from those associated with other structured management practices or investment in IT, though the latter is an important complement. Moreover, instrumental variables estimates and timing falsification tests suggest a causal relationship. Implications for firm strategy, however, are nuanced; we find evidence of significant advantages for early adopters of DDD, particularly in the 2005-2010 window, when adoption rates in the sector were lower. Yet we also observe timing-dependent complementarities. The frontier of data-centric practices shifts during our study period, with increased use of predictive analytics becoming the key driver of productivity gains from 2010 to 2015.

The adoption and use of emerging and smart technologies like robotics is a key concern as the advanced economies undergo the latest technological revolution. While firms and factories often adopt technologies like robotics and advanced manufacturing techniques at a fast rate, government agencies are often seen as lagging in their adoption of such tools. We offer evidence about the adoption of robotics from the case of American crime laboratories. Using data from the census of crime labs, we show that the adoption of such technologies depends on traditional drivers of agency capacity and demand: budgets, the agency’s task environment, and its relative level of professionalism. Together these findings suggest that agencies can be early adopters of such technologies if they have the capacity (and need) to do so.

We study funding mechanisms for new ventures based on cryptographic tokens enabled by blockchain technology, such as initial coin offerings (ICOs). The infrastructure built around blockchain allows for efficient trading of these tokens. Thus the due diligence process can be crowdsourced beyond the potential early adopters, as favorable assessments of the venture can be leveraged with speculative token purchases exceeding the buyer's individual demand. We develop a model for an entrepreneur considering digital tokens to finance a new venture, focusing on token tradability and broader crowdsourcing of due diligence. We then compare funding via digital tokens with funding from traditional financing sources like venture capital as well as with pre-sale crowdfunding with non-tradable rewards. We find that tradable digital tokens are more attractive when there is higher uncertainty about market demand, which is frequently the case when developing applications of new technologies, such as blockchain-based platforms. In such cases crowdsourcing due diligence benefits from the information contained in the private valuations of the early potential adopters. Token tradability leverages that information and increases the amount that can be financed, thus enabling new ventures with higher development costs. The increased funding comes at the cost of a lower digital token price and lower total profit for the entrepreneur, but may still be preferable to the alternatives, if such alternatives are available at all. This work makes a contribution to the emerging literatures on digital cryptographic tokens and on crowdfunding new ventures.

Blockchain is a special type of database that cannot be easily manipulated or hacked. Sometimes called distributed ledger technology, the database is shared by many computers, called nodes. The components of the database are broken up into blocks or sheets. One of the ingenious ideas is that the end of each block contains a cryptographic signature. This signature (sometimes called a digest or a hash) summarizes all the information in the block, and any trivial change in the data in the block causes the signature to be completely different. This last line of the block is then repeated as the first line of the next block — which is where the “chain” comes in. This feature makes a blockchain immutable. If anyone tries to edit an old block (rewrite history), the block signature will change, and the network will see that the block signature does not match the first line of the next block. The network throws out the corrupted block and automatically replaces it with the original. Hence, it is practically infeasible to alter history to commit fraud or unwind unwanted transactions. Given that most of the blockchain applications have been focused in finance, the technology has been largely under the radar screen in marketing. We argue that blockchain will fundamentally impact the practice of marketing. There are potentially large rewards for the early adopters in marketing — and costs for those left behind by this innovation.

Research Question/IssueWe study reward crowdfunding (RC), the most innovative segment of the crowdfunding market, where, instead of a debt or equity contract, fund providers are promised some good or service in the future in exchange for their contribution to the funding of the investment project under a contract that does not penalize the creator's failure to deliver. The existing economic and legal literature is puzzled by the platform's use of this seemingly inefficient contract where a standard pre-sale contract would appear to work better. Research Findings/InsightsCounterintuitively, we prove that the no-penalty contract is the optimal contract between creators of unknown talent and early adopters of their products when creators can benefit from being discovered as talented and from the goodwill generated by delivering on their promise to early adopters. Theoretical/Academic ImplicationsOur analysis contributes to understanding RC by showing that the no-penalty RC contract, far from being an inefficiency, is a contractual innovation specifically designed for talent discovery. We also contribute to the literature on relationship contracts, showing that even in a one-shot game, it is possible to sustain a contract in the desire to build a reputation that will be useful in a future contract with a third party. Practitioner/Policy ImplicationsOur analysis has important policy implications on how backers should be protected. Standard measures of consumer or investor protection may be counterproductive. María Gutiérrez‐Urtiaga gratefully acknowledges the financial support from Comunidad de Madrid and the EU's European Social Fund through grant S2015/HUM‐3353 EARLYFIN‐CM and from the European Regional Development Fund through grant FEDER UNC315‐EE‐3636.

In this study, we investigate a seller's voluntary disclosure strategy when serving two groups of consumers who arrive sequentially and are reference dependent with respect to product quality. Consumers may be naive or sophisticated, depending on whether they can make rational inferences from the seller's disclosure behavior and an experienced consumer's quality review. We show that when consumers are naive, the seller can strategically withhold high‐quality information and disclose low‐quality information to boost the reference‐dependent early adopter's subjective quality review, which in turn enhances the follower's quality expectation and allows the seller to extract more surplus in the second period. However, when consumers are sophisticated, it is difficult for the seller to enhance their quality expectations by designing his disclosure strategy to manipulate the early adopter's quality review. The seller discloses all the quality information to consumers. When the market contains both naive and sophisticated consumers, the seller is able to withhold relatively low‐quality information in advance. In such a situation, the seller exclusively serves naive customers in the first period by charging a high retail price. The earlier results are quite robust, regardless of whether the review rating is bounded or whether consumers possess heterogeneous preferences with respect to product quality.

Do social networks matter for the adoption of new forms of political participation? We develop a formal model showing that the quality of communication that takes place in social networks is central to understanding whether a community will adopt forms of political participation where benefits are uncertain and where there are positive externalities associated with participation. Early adopters may exaggerate benefits, leading others to discount information about the technology's value. Thus, peer effects are likely to emerge only where informal institutions support truthful communication. We collect social network data for sixteen Ugandan villages where an innovative mobile-based reporting platform was introduced. Consistent with our model, we find variation across villages in the extent of peer effects on technology adoption, as well as evidence supporting additional observable implications. Impediments to social diffusion may help explain the varied uptake of new and increasingly common political communication technologies around the world.

The 3rd Annual European Alternative Finance Report presents the most comprehensive analysis of the status of alternative finance industry in Europe, covering more countries, alternative finance models, as well as industry trends and developments than was available in its predecessors. Much effort has been placed on data quality verifications and clarifications in an ongoing productive and collaborative dialogue with all platform informants and research partners. Here, we wish to acknowledge their invaluable contributions, without which this report could not have been written. Overall, the data collected shows that 2016 saw European alternative finance doubling its volumes from 2015, and continuing an impressive growth. When placed into its short historical perspective, an impression emerges of an industry progressing from an introduction stage catering to innovators, into the growth stage catering to a growing number of early adopters. This growth phase is characterized by entry of new platforms and service providers, overall increasing competition, emergence of first cases of consolidation, diversification of products, and investments in process effectivization and streamlining. Despite exhibiting continuous healthy growth, Europe still punches well below its potential in most countries. Challenges remain both in terms of market education, and amendments of regulation. In Europe regulatory challenges are faced with two barriers. First, most countries have relatively mature and well-established regulatory systems. And, second, these vary significantly across countries. In this respect, our study provides initial evidence that more favorable regulation at national level is associated with higher volumes per capita, as well as with higher share of funding reaching businesses. Accordingly, one can expect that if regulatory conditions will continue to improve at both national and international levels, the industry will be able to maintain and enhance its growth. Nevertheless, one should acknowledge that the story of European alternative finance sector growth, more importantly, is the story of the democratization of access to finance and investment opportunities for people and ventures in Europe. When we present that the industry has generated EUR 2 Billion in 2016, it implies that close to 95% of this sum was actually invested in European venturing reaching businesses, entrepreneurs, artists, and social activists. All aim at creating value to consumers, investors and society via ventures made possible thanks to the support of the crowd. Accordingly, and by extension, more accommodating regulation for the industry, also implies greater access to finance for multiple stakeholders in the economy and more opportunities for value creation. Here, our findings leave much room for optimism for the coming years. Not only are volumes growing strongly, but platforms are investing actively in innovative solutions towards improving performance and customer service. Moreover, evidence suggests that a greater share of platforms engage in cross-border transactions, although, in most cases, these still represent a relatively modest share of overall volumes (thanks to limitations mentioned above). Finally, we hope this report, and the insights emerging form it, will be of help to all stakeholders interested in the development of alternative finance in Europe. And we look forward to a continued cooperation with all our partners in monitoring industry developments in the future.

We study whether social media can contribute to hatred against minorities with a focus on Donald Trump's political rise. To establish causality, we construct an instrument for Twitter usage based on the platform's early adopters at the South by Southwest (SXSW) festival in 2007, who were crucial for Twitter's diffusion across US counties. Instrumenting with the home counties of SXSW followers who joined in March 2007, while controlling for the counties of SXSW followers who joined before the festival, we find that a one standard deviation increase in Twitter usage is associated with a 32% larger increase in anti-Muslim hate crimes since the 2016 presidential primaries. Further, Trump's tweets about Islam-related topics predict increases in xenophobic tweets by his followers, cable news attention paid to Muslims, and hate crimes on the following days. These correlations persist in an instrumental variable framework exploiting that Trump is more likely to tweet about Muslims on days he plays golf.

Platform-specific digital tokens are becoming increasingly common with the proliferation of initial coin offerings (ICOs). In addition to a novel financing mechanism, such tokens can help address the coordination problem that is common in network adoption. We develop a model to investigate the use of tradable digital tokens to solve this coordination problem. Our analysis shows that platform-specific tokens, due to their tradability and consequent higher value if the platform succeeds, can provide another tool to overcome the coordination problem in a platform adoption setting and to support equilibria favorable to the platform. We find that if the platform is not facing capital constraints, the most profitable strategy is the traditional strategy to subsidize adoption. If the platform is capital constrained, however, then token issuance provides an alternative that is increasingly attractive as the platform's cost of capital increases. With tokens, the platform trades off future revenue for present revenue, which helps finance solving the coordination problem. In that sense, even pure utility tokens have certain characteristics of equity: (1) early adopters share the future gains if the platform succeeds, and (2) the tokens provide an alternative when traditional financing is too costly or not available to the platform.

While the importance of organizational learning and technological innovation for environmental sustainability is well noted, little is known about why and how firms choose not to implement what they learn and innovate. We examine the learning-doing gap in an empirical context of sustainable innovation and environmental technologies, the domain where social constituents increasingly consider environmental performance to be significant evaluative criteria. Building upon institutional perspectives, we suggest that the increased popularity and social attention toward sustainable innovation may serve as externally imposed pressures that are difficult for firms to ignore, thus leading to the creation and development of novel technologies aligned with the normative pressures. Our key argument is that such technologies are not fully implemented, a situation referred to as decoupling. This argument is empirically supported by our analysis of data from the Green Certification Program, a relatively new, government-initiated certification system for legitimating green technologies in Korea. More importantly, we find that decoupling is further differentiated in terms of adoption timing between initial innovators and early adopters, two groups of firms that develop different risk perceptions of the consequences of certification implementation. Implications for organization studies, sustainable innovation, and environmental policies are discussed.

Recent technological advancements—such as faster computing, better algorithms, and more robust communication networks—have made it easier and cheaper to collect, store, analyze, use, and disseminate data. These changes have led to the emergence of the data economy: an economy where success depends on how effectively firms can leverage data to generate insights and unlock value. Better use of data will be a crucial driver of economic and societal progress in the coming decades. The widespread adoption of data analytics and artificial intelligence is expected to contribute hundreds of billions of dollars to U.S. GDP in the coming years in sectors such as finance, transportation, and manufacturing, while unlocking new opportunities to improve outcomes in fields such as education and health care. In addition, the growing adoption of the Internet of Things—ordinary objects embedded with sensors and connected to the Internet—is unleashing a wave of innovation and growth as billions of devices that collect and use data come online. And state and local leaders are investing in smart cities to leverage data to create sustainable, resilient communities. Given the significant economic and social impact of these developments, policymakers should be leading the charge to enable data-driven innovation in their states. This effort should encompass not just the development and growth of data-driven companies, but also the use of data to address their states’ most important priorities, such as improving health care, reducing crime, developing sustainable communities, and improving schools. While data-driven innovation is a global phenomenon, some regions are better poised to enjoy the resulting benefits because they have invested in and supported the conditions necessary to succeed in the data economy. This is also true within the United States, where some states are actively building the necessary foundation for a thriving data economy and others are lagging. Decisions made today that affect the extent to which a state participates in the data economy will have long-term implications for its future growth, as data plays an increasingly larger role in many different sectors across the economy. Early adopters will benefit more quickly from using data to address a multitude of challenges, and by positioning themselves at the forefront of data-driven innovation; they also will be able to grow and attract data-driven companies in a wide range of sectors that will make them the future hubs of the data economy. This report uses 25 indicators across three categories to assess which states are doing the most to encourage and enable data-driven innovation. These categories are: - Data: the extent to which key datasets are available, including data about the government, education, health care, and energy; - Technology: the availability of key digital infrastructure, such as broadband, smart meters, and electronic health records; and - People and companies: human and business resources, such as the number of open-data companies in the state, and the size of the data professional community. State policymakers should support all three areas to successfully enable data-driven innovation. First, states should take steps to guarantee that data is available for use, such as by ensuring government agencies collect and release high-value datasets. Open government data promotes transparency, encourages citizen collaboration, and creates value through innovation and efficient decision-making. Making data available can also provide the private sector with the building blocks necessary to develop new products and services. For example, the Chicago-based start-up SpotHero, which makes a mobile app to help drivers find and reserve parking spots, relied heavily on open government data for its initial development. Government agencies can also use data to improve their services and be more efficient. For example, with no additional investment, Oregon’s state marine board used its state’s open data platform to replace its biennial boating handbook, which cost $150,000 to produce every two years, with a live, interactive map with location-specific regulations, docks, service stations, and navigation instructions for boaters. The U.S. Department of Commerce estimates that the private sector uses government data to generate annual revenues of as much as $221 billion annually. And, globally, the McKinsey Global Institute estimates that open data has the potential to create $3 trillion to $5 trillion per year in additional value across education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance sectors. Second, states should enable the deployment of the technology platforms that underpin success in the data economy. This includes facilitating the deployment of digital infrastructure, such as fixed and mobile broadband Internet, plus data platforms such as intelligent transportation systems, electronic health records, and smart meters. In addition, states should consider how they can support the development of the Internet of Things, particularly the development of smart cities that use data collected by sensors on physical infrastructure and digital transactions with government agencies. Third, state economic development efforts should include a focus on the data economy and helping transform existing industries to make better use of data. For example, better use of data and analytics in health care—to allow doctors to make better medical decisions and provide better preventative care—could slash costs by up to $450 billion. Reforms can start with developing the human capital necessary for data-driven innovation to thrive, and supporting businesses participating in the data economy. Virtually every sector of the economy can benefit from better use of data. But the growth of data-driven enterprises will be limited by the availability of workers with in-demand data skills. To this end, states should promote the growth of data-driven businesses by improving educational offerings in data science and related fields. This begins at the K-12 level, where strong math and computer-science training can equip students with the skills necessary for advanced data literacy, and continues through higher education, where degrees in technical fields can provide the highly skilled workforce needed to participate in the data economy. States should also strengthen connections among businesses, government agencies, and universities to encourage collaboration and learning among those working on data-related projects across a diverse range of industries.

Recent years have seen a rush toward evidence-based tools in criminal justice. As part of this movement, many jurisdictions have adopted actuarial risk assessment to supplement or replace the ad-hoc decisions of judges. Proponents of risk assessment tools claim that they can dramatically reduce incarceration without harming public safety. Critics claim that risk assessment will exacerbate racial disparities. Despite extensive and heated rhetoric, there is virtually no evidence on how use of this “evidence-based” tool affects key outcomes such as incarceration rates, crime, or racial disparities. The research discussing what “should” happen as a result of risk assessment is hypothetical and largely ignores the complexities of implementation. This Article is one of the first studies to document the impacts of risk assessment in practice. It evaluates pretrial risk assessment in Kentucky, a state that was an early adopter of risk assessment and is often cited as an example of best-practices in the pretrial area. Using rich data on more than one million criminal cases, this Article shows that a 2011 law making risk assessment a mandatory part of the bail decision led to a significant change in bail setting practice, but only a small increase in pretrial release. These changes eroded over time as judges returned to their previous habits. Furthermore, the increase in releases was not cost-free: failures-to-appear and pretrial crime increased as well. Risk assessment had no effect on racial disparities in pretrial detention once differing regional trends were accounted for. Kentucky’s experience does not mean we should abandon risk assessment, but it should temper the hyperbolic hopes (and fears) about its effects. Risk assessment in practice is different from risk assessment in the abstract, and its impacts depend on context and details of implementation. If indeed risk assessment is capable of producing large benefits, it will take research and experimentation to learn how to achieve them. Such a process would be evidence-based criminal justice at its best: not a flocking toward methods that bear the glossy veneer of science, but a careful and iterative evaluation of what works and what does not.

Consumer reviews may have perverse effects, including delays of adoption in new products of unknown quality when consumers are boundedly rational. When consumers fail to take into account that past reviewers self-select to purchases, a monopolist may manipulate the posterior beliefs of consumers who observe the reviews, because the product price determines the self-selection bias. The monopolist will charge a relatively high price because the positive selection of the early adopters increases the quality reported in the reviews.

This paper offers a demand-based theory of how platform maturity affects the adoption of platform complements. We argue that differences between early and late adopters of the platform include willingness to pay for the platform-and-complement bundle, risk preferences, preference for novelty, and search behavior. These differences create heterogeneous demand conditions for complements that affect both average complement performance and variance in the types of complements that are more or less successful. Using a novel data set of 2,921 sixth-generation console video games, we find that platform maturity has a negative relationship on video games’ unit sales. Furthermore, as the platform matures, we find that the sales disparity between new intellectual property (IP) games and games based on existing video game properties or media tie-ins grows to the detriment of new IP games. We find that the sales disparity between superstar games and flops also widens as the platform matures. These effects are accentuated by the introduction of a next generation platform, which further skews the complement's customer pool as early adopters migrate away from the current generation platform. Robustness tests that control for unobserved heterogeneity help rule out alternative explanations and support our argument that these performance implications are truly driven by heterogeneity in demand.

A body of literature shows the destabilizing role of ICT and change from analogue to digital in the cultural industries in general, and in press industry in particular. This literature demonstrates that constant experimentation and innovation in the area of organizational arrangements and business models (BM) has become a key competitive advantage. As a result, traditional BMs, which were dominant and stable in different cultural industries (such as media, film, music, publishing etc), have given rise to a multiplicity of arrangements in business management and the emergence of disruptive and innovative business models, which often successfully coexist in the same market segment. According to this view point, strategic and structural change is necessarily driven by competition or the need for efficiency. However alternative theories predicts that in depending on the industry structural characteristic, only early adopters of innovation may be driven by a desire to improve performance, whereas as an innovation spreads and organizational field becomes more established, there may be a push towards homogenization. The case of the French press is quite symptomatic of that standpoint. From the empirical analysis of 100 press websites observed over the period from 2004 to 2014, the paper substantiates the convergence process towards three dominant clusters of online BMs: “A minima Digital”, “Freebie Plus” and “Exploring Leaders”. Using a Random Effects Probit econometric model the paper puts forward that this isomorphic process is mainly due to the fact that mimetic behavior over-weights search for performance in French press.

At the World Economic Forum more than 800 executive and technology experts were asked when they thought a particular “tipping point” would be reached – when would we see a government collect tax with blockchain? The agreed date was 2023 (on average). A full 73% of the respondents however, expected the tipping point to have been reached by 2025.This paper argues that the EU VAT will be an early adopter, if not the earliest adopter of blockchain. There are a number of reasons why. Blockchain will bring substantial efficiencies to VAT collection. It will reduce costs, and build critical inter-governmental trust relationships. Most importantly, blockchain will immediately end revenue losses well in excess of €50 to €60 billion per year in missing trader intra-community fraud (MTIC).Blockchain will also be essential for making the EU Commission’s April 2016 Action Plan on VAT work. Blockchain should be a critical part of the detailed legislative proposal (expected in 2017). This plan will bring in a “definitive VAT system” dealing with intra-EU cross-border trade, which will be based on taxation in the country of destination. This paper predicts that the EU will bring in the “definitive system” on the back of blockchain technology.Blockchain is a revolutionary improvement on any centralized data system. Tax administrations are inherently based upon centralized repositories of taxpayer data. They are prime candidates for the kinds of efficiency improvements that come through blockchain. This is particularly the case for transaction taxes, and even more so for a VAT fraud prevention application, like the Digital Invoice Customs Exchange (DICE), which relies on a real-time exchange of encrypted data.

The Extractive Industries Transparency Initiative (EITI) originated in the international domain but can only operate if adopted at a national scale. How EITI unfolds in a particular country is thus a consequence of the particular interactions between domestic and transnational political processes, and among ideas, institutions and political interests existing at these different national and transnational scales. National politics is especially crucial to the forms taken by EITI. This paper addresses how national political settlements have led to diverse responses to EITI across three Andean countries: Peru (an early adopter); Colombia (a late adopter); and Bolivia (a non-adopter). We argue that national elites have taken up (or, in the case of Bolivia, rejected) EITI as part of a strategy to secure broader goals and to convey particular messages about the state of democracy and political priorities in their countries, including towards actors on the international stage. We conclude that the EITI, and the idea of transparency, are leveraged by national actors to meet domestic political goals and interests, even as these may also be intertwined with other international pressures and contexts. While EITI, and arguments over transparency, can affect the nature of the domestic political settlement, they do so primarily by helping deepen domestic political changes that are already underway and that were the same political changes that created the initial space for EITI.

Despite a high volatility and the recent fall in price, more and more merchants and consumers adopt Bitcoin. The virtual currency might be standing at its critical point to reach the early majority of adopters. This paper examines whether an application called ChangeTip has the potential to catalyze the breakthrough of Bitcoin. We assume a strong linkage between the diffusion of ChangeTip and Bitcoin so that we can directly deduce the impact of this application on Bitcoin. Results from a conducted online survey of 210 potential early adopters indicate that the diffusion of ChangeTip has the potential to advance the diffusion of Bitcoin to mainstream markets. We found that performance expectancy is the key driver for the intention to recommend ChangeTip. Also, effort expectancy, social influence and facilitating conditions are important factors for recommending ChangeTip. Concerning the intention to use ChangeTip in the future, performance expectancy and social influence are the main drivers. Furthermore, facilitating conditions are important for using ChangeTip. In addition, an analysis of the non-user of Bitcoin and ChangeTip was conducted. Theoretical and practical implications of these results are discussed.

This paper reviews three decades of gender quota policies in Germany and assesses policy adoption in parties, public administration, as well as on corporate and public boards. Germany was an early adopter of quotas for women in political parties and in public administration. Even though both measures were controversial when first enacted in the 1980s and early 1990s, they have since become rather low-profile gender equality strategies. A recent initiative to adopt quotas for women on corporate and public boards, by contrast, produced substantial public discussion. The mainstreaming of positive action plans in public institutions that include decision quotas, fixed quotas and goal quotas has given gender advocates formally strong leverage to advance a gender equality agenda. At the same time, a culture of minimalist compliance has pervaded the public sector and parties. Male institutions and organizations tend to exhibit more passive resistance than vocal opposition, thus making it difficult for feminists to engage effectively with non-compliance. A lack of sanctions as well as intricate strategies to circumvent quota decisions add to a sense among German feminist activists that quotas are one, but by no means the only strategy for gender equality in public life.

The Data Protection Act 1998 (DPA) is the only piece of English legislation which is specifically directed at protecting personal information and an individual’s privacy in respect of it. Celebrities were “early adopters”, testing its effectiveness with cases like Campbell, Douglas and Murray. In each of those early cases, while the data protection claim was pleaded in the action, it was relegated to being little more than a footnote in the final result. In both Campbell and Douglas the DPA damages were assessed at £50. Supermodels are not the only celebrity litigants to need the prospect of more than that to get out of bed to litigate. The 10 years since Campbell has - as a result - seen a Promethean struggle to kindle the fire of the DPA’s potency and effectiveness. Also, as a result of the recent misuse of private information damages case of Gulati & others v MGN (where a total of £1.2m was awarded to 8 celebrities) the scope for damages in this area has been radically re-calibrated.

We examine firms' motivations for implementing grandfather clauses that allow certain consumers to continue access to a service at a favorable, but no longer available price. We find that when consumers are fully cognizant of their valuations for available product alternatives, firms are typically better off offering all potential consumers the optimal uniform price. However, if grandfathered consumers are made complacent, failing to reevaluate the service over time, grandfather clauses may permit firms to profitably price discriminate between early adopters and new consumers in exchange for forfeiting the right to optimally set prices for early adopters.

In this paper, we examine how a seller sells a product/service with a positive consumption externality, and customers are uncertain about the product's/service's value. Because early adopters learn this value, we consider the customers' intrinsic signaling incentives and positive feedback effects. Anticipating this, the seller commits to provide price discounts to the followers, and charges the leader a high price. Thus, the profit-maximizing pricing features the cream skimming strategy. We also show that the lack of seller's commitment is detrimental to the social welfare; nonetheless, the sequential selling still boosts up the seller's profit. Embedding a physical network with arbitrary payoff externality among customers, we investigate the optimal targeting strategy in the presence of information asymmetry. We provide precise indices for this leader selection problem. For undirected graphs, we should simply choose the player with the highest degree, irrespective of the seller's commitment power. Going beyond this family of networks, in general the seller's commitment power affects the optimal targeting strategy.

Hybrid business models are an emerging phenomenon that employs market tactics to address social and environmental issues. The B Corp model is one form of a hybrid model, with the first B Corp certified in the USA in 2007. It has emerged, in part, in response to recent global financial crises and low levels of trust in corporations. The B Corp model is a for-profit, socially obligated, corporate form of business, with traditional corporate characteristics but also with societal commitments. This report discusses the outcomes of a study into how the B Corp model is emerging in Australia. The purpose of this study was largely exploratory – few academic studies have investigated B Corps and the first Australian B Corps were only certified in 2012. This report captures the experiences of the early adopters of the B Corp model in Australia: their approach to business; their motivation for adopting the B Corp model; the benefits and challenges of implementing the model; how they measure success; and, how the B Corp model could become more widespread. Fourteen B Corps participated in the study. The research data revealed a consistency of views about the primary aim of the B Corps, which can be summarised as profit with a purpose – making profits to create positive social and/or environmental impacts. The key motivation for certifying as a B Corp was the alignment of values and a formal validation of the companies’ business philosophy and approach. The ability to connect with like-minded businesses and the potential for inter-B Corp business development was attractive to B Corps, acknowledging the high level of trust generated by the shared values of the B Corp network. While the B Corp label was a strong driver, it is early days and major tangible benefits are yet to be realised. The B Corps identified few barriers for implementing the B Corp model in Australia, but larger B Corps hinted at challenges with changing the culture of the organisation to align all employees with the B Corp values. Success was not gauged by maximising profits for owners/shareholders, but the impacts the businesses are making. Profits are a means to achieve positive social and environmental contributions. Without government support for the B Corp model (through legislative changes or mechanisms such as tax incentives), mainstreaming the model will take time and will require increasing advocacy, awareness-building and education, and lobbying powerful stakeholders such as government directly and/or through coalitions such as industry bodies.

This paper is a study into some of the regulatory implications of cryptocurrencies using the CAMPO research framework (Context, Actors, Methods, Methods, Practice, Outcomes). We explain in CAMPO format why virtual currencies are of interest, how self-regulation has failed, and what useful lessons can be learned. We are hopeful that the full paper will produce useful and semi-permanent findings into the usefulness of virtual currencies in general, block chains as a means of mining currency, and the profundity of current ‘media darling’ currency Bitcoin as compared with the development of block chain generator Ethereum. While virtual currencies can play a role in creating better trading conditions in virtual communities, despite the risks of non-sovereign issuance and therefore only regulation by code (Brown/Marsden 2013), the methodology used poses significant challenges to researching this ‘community’, if BitCoin can even be said to have created a single community, as opposed to enabling an alternate method of exchange for potentially all virtual community transactions. First, BitCoin users have transparency of ownership but anonymity in many transactions, necessary for libertarians or outright criminals in such illicit markets as #SilkRoad. Studying community dynamics is therefore made much more difficult than even such pseudonymous or avatar based communities as Habbo Hotel, World of Warcraft or SecondLife. The ethical implications of studying such communities raise similar problems as those of Tor, Anonymous, Lulzsec and other anonymous hacker communities. Second, the journalistic accounts of BitCoin markets are subject to sensationalism, hype and inaccuracy, even more so than in the earlier hype cycle for SecondLife, exacerbated by the first issue of anonymity. Third, the virtual currency area is subject to slowly emerging regulation by financial authorities and police forces, which appears to be driving much of the early adopter community ‘underground’. Thus, the community in 2016 may not bear much resemblance to that in 2012. Fourth, there has been relatively little academic empirical study of the community, or indeed of virtual currencies in general, until relatively recently. Fifth, the dynamism of the virtual currency environment in the face of the deepening mistrust of the financial system after the 2008 crisis is such that any research conclusions must by their nature be provisional and transient. All these challenges, particularly the final three, also raise the motivation for research – an alternative financial system which is separated from the real-world sovereign and which can use code regulation with limited enforcement from offline policing, both returns the study to the libertarian self-regulated environment of early 1990s MUDs, and offers a tantalising prospect of a tool to evade the perils of ‘private profit, socialized risk’ which existing large financial institutions created in the 2008-12 disaster. The need for further research into virtual currencies based on blockchain mining, and for their usage by virtual communities, is thus pressing and should motivate researchers to solve the many problems in methodology for exploring such an environment.

When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when gents are connected by a network and a monopolist seller chooses a policy to maximize profits. Consumers with low degree (few friends) have incentives to adopt early, while consumers with high degree have incentives to free ride. The seller can induce high-degree consumers to adopt early by offering referral incentives - rewards to early adopters whose friends buy in the second period. Referral incentives thus lead to a `double-threshold strategy' by which low and high-degree agents adopt the product early while middle-degree agents wait. We show that referral incentives are optimal on certain networks while inter-temporal price discrimination (i.e., a first-period price discount) is optimal on others, and discuss welfare implications.

In the United States (US) and Europe, and indeed, globally, pharmaceutical companies are facing rapidly evolving regulatory and reimbursement evidentiary expectations linked in large part to the clinical and economic realities confronting their respective healthcare systems. Specifically, demands for comparative effectiveness research (CER) and relative effectiveness (RE) evidence have been driven by: (1) health care spending pressures; (2) lack of information to guide the efficient use of new technologies; and (3) consequent political momentum to promote enhanced generation of evidence to inform post-regulatory clinical and coverage decision-making. CER (the term commonly used in the US) and RE (the term commonly used in Europe) both share a focus of producing evidence about how treatments work compared with existing alternatives under circumstances of usual care. The purpose of this work has been to ascertain how the current drug development paradigm at five global pharmaceutical companies is evolving in response to perceived demands for evidence of comparative effectiveness and relative effectiveness, in particular, from payers and HTA bodies, but also from clinicians and patients. To accomplish this goal, we first undertook a targeted literature review (primarily to provide context and help to identify some themes for the interview programme), followed by a semi-structured interview program with an international sample of 19 senior executives (12 identified as CER experts and seven as RE experts). These executives hold positions in clinical development; health economics and outcomes research (HEOR); medical affairs; and pricing, access and reimbursement (PAR) across five global pharmaceutical companies. Our goal was to develop more detailed information about how these organisations currently conceptualise CER/RE, how they have begun to modify their internal processes to respond accordingly, and what they perceive to be the enablers and barriers for continued adaptation in response to both internal and external factors confronting the pharmaceutical industry. Both tasks have revealed a number of common emerging themes regarding both CER and RE, and more importantly,how companies are adapting to this new environment which is elevating the importance of information needs of these post-regulatory decision makers. First, the current drug development paradigm has already started to change in response to CER/RE evidence demands from stakeholders. These changes range from inclusion of active comparators in clinical trials, involvement of stakeholders to help define key phase IIb and III study design features, incorporation of PRO measures and earlier planning for phase IV studies. It is also true, however, that some of these changes do not deliver on all the elements of CER/RE, particularly the “under usual circumstances of care” dimension. However, our key informant interviews highlighted the need for industry to improve on current methods for eliciting the patient perspective,as their current conceptualisation of CER/RE tends to be primarily payer-focused. Second, CER/RE investments are being made at different phases depending on the company. Not surprisingly, however, CER/RE investments currently lag behind the phases of initial evaluations. Such evaluations typically involve project team discussions with representatives from HEOR and PAR. Issues such as the development of initial product profiles and models of expected product effects on clinical outcomes relative to alternative treatments are discussed. If the investigational compound progresses beyond these initial evaluations (including the requisite safety and early efficacy requirements), then typically the project team leader would advocate for the incremental investments to be made in the clinical development program to support CER/RE data collection. The degree to which they focus on this currently in the US as compared to Europe is less, given that the EU has a longer experience of responding to the demands of national HTA/pricing and reimbursement bodies. Third, a number of barriers have been identified in terms of incorporating CER/RE considerations into companies’ drug development plans. While we spoke to a group of individuals that could be characterised as “early adopters” of CER/RE, they identified a number of existing internal barriers to the successful integration of CER/RE within companies. Barriers included a lack of clear accountability for incorporating CER/RE considerations into development plans, and lack of incentives, as well as the high costs of undertaking such studies. However, some of these costs may be mitigated by increased use of observational studies and electronic health record data. However there will need to be additional investments in the research infrastructure to conduct CER/RE as well as on-going methods development and dialogue to ensure regulatory acceptability for promotion of study results in the US. Another barrier raised was the lack of shared understanding on the development team of the importance of external demands for CER/RE data, together with the lack of confidence amongst scientific staff that today’s experts have sufficient methods or adequate data to generate robust/valid data from CER/RE studies. Fourth, a number of facilitators to the successful integration of CER/RE were identified, including an internal champion, often a very senior member of the company who could provide leadership and support, the ability to attract and retain top talent to lead the CER/RE research effort, and external pressures and drivers for CER/RE. Fifth, there was universal agreement on the part of our interviewees that by the year 2020, CER/RE would have a much greater role in influencing the process of drug development as compared to today. However the question remains as to whether the industry’s incremental investments in CER/RE will have the anticipated positive return on investment in terms of reimbursement and market access.

Using international data on porting, churn, and mobile prices, this paper seeks to estimate the impact of a change in the efficiency of a mobile-number-portability (MNP) regime. It offers new empirical evidence, consistent with prior findings in the literature, that the average time it takes to port a mobile line is positively and statistically significantly correlated with wireless prices. Measured by days to port, the United States boasts the most efficient MNP regime in the world, with average porting times of roughly two hours. By comparison, the average porting time among all “early adopters” in the sample — countries that embraced MNP by 2005 — is 6.6 days. Regardless of a country’s existing level of efficiency, any delay in porting times is predicted to increase wireless prices. Thus, even a relatively efficient country such as the United States may incur higher prices in response to a diminution in MNP efficiency.

Barcode scanners, introduced in the early 1970s, were a foundational process innovation in the grocery supply chain. By 1984 scanners had been installed in 10% of food stores in the U.S. Difference-in-difference analysis of city-level price data shows that scanners reduced prices of groceries by about 1.4% in their first decade. The results are consistent with prior estimates of labor saving by scanners and better information available to stores. Early adopters and adopters in states that imposed fewer restrictions on complementary process innovations contributed disproportionately to the price decreases.

Massive open online courses (MOOCs) have commanded considerable public attention due to their sudden rise and disruptive potential. But there are no robust, published data that describe who is taking these courses and why they are doing so. As such, we do not yet know how transformative the MOOC phenomenon can or will be. We conducted an online survey of students enrolled in at least one of the University of Pennsylvania’s 32 MOOCs offed on the Coursera platform. The student population tends to be young, well educated, and employed, with a majority from developed countries. There are significantly more males than females taking MOOCs, especially in BRIC and other developing countries. Students’ main reasons for taking a MOOC are advancing in their current job and satisfying curiosity. The individuals the MOOC revolution is supposed to help the most — those without access to higher education in developing countries — are underrepresented among the early adopters.

This article examines the growth of vacant property registration ordinances (VPROs) in the U.S. It utilizes a new, unique database of local VPROs enacted in the U.S. The database is based on an industry listing of ordinances maintained by a large, national field services firm employed by mortgage lenders to secure and maintain foreclosed properties. Copies of over 550 ordinances (or in a few cases, summaries of ordinances) were obtained and coded on over 30 characteristics. Initial analysis of the database reveals that VPROs grew dramatically in 2008 and 2009, during the climax of the national foreclosure crisis, and that number or ordinances continued to grow after 2009, albeit at a somewhat slower pace. Growth was particularly robust in the Midwest, Southeast and West, although growth occurred in all parts of the country generally. Localities in some states, especially California, were particularly early adopters of VPROs in 2007 and 2008. In general, higher foreclosure levels do predict higher rates of VPRO adoption within a state, but only roughly, with a good deal of variation not explained by foreclosure rates. In particular, a few states that have been hit hard by foreclosures (Arizona and Nevada, e.g.) did not see substantial growth in the number of VPROs. The coverage, requirements, and penalties specified in VPROs vary greatly across ordinances and across regions of the country.

This study investigates which candidates were more likely to adopt Facebook, YouTube, and Twitter in the 2010 elections to the U.S. Congress and the reasons why. The study makes three contributions. First, it compares and analyzes three different social media whose technology attributes differ in ways that prove relevant to adoption decisions and, we project, to the extent and nature of their usage. Second, we use diffusion of innovation theory to derive testable hypotheses predicting adoption and explaining our results. Third, we rely on nearly 100 interviews with candidates and campaign staff members to refine our hypotheses and provide a richer explanation for the motivating factors. The interviews reveal that candidates are both content providers and adoption decision-makers who are concerned about image and credibility. We find that large majorities of the major party candidates for the House of Representatives had a Facebook page, Twitter account, and YouTube channel. Candidates who raised the most money and those who had familiarity with earlier generations of online media were the most likely early adopters. Constituency demographics did not influence the likelihood of adopting Facebook, Twitter, or YouTube, however. We found some differences in adoption across social media. Republicans were significantly more likely than Democrats to have adopted YouTube, but there were no party differences for Facebook and Twitter. YouTube also differed in that while competitiveness of the race increased adoption, peer adoption had no effect. Finally, incumbents were significantly more likely to have adopted Facebook and YouTube, but for the newest social media application, Twitter, incumbents were the least likely to be early adopters.

Referral rewards programs are traditionally argued to be valuable in fostering word-of-mouth communication. However, they may also help to mitigate the coordination problem in the adoption of a new product that displays network externalities in consumption, by insuring early adopters against the risk that other consumers will wait-and-see. This paper analyzes a model that isolates this insurance purpose of referral rewards. A sufficiently generous referral reward can indeed incentivize early adoption, but this could be costly if not all consumers initially know about the product. The smaller the pool of potential early adopters relative to the population and the stronger network effects, the more likely it is that a price menu that includes referral rewards sufficient to overcome coordination failure is unambiguously beneficial for the firm.

We examine the determinants of the timing of and financial instruments involved in banks’ initial fair value option (“FVO”) elections upon their adoption of SFAS No. 159. We focus on regular (in 2008:Q1) adopters of the standard, and distinguish their FVO elections from those of early (in 2007:Q1) adopters. Song (2008), Henry (2009), and Guthrie, Irving, and Sokolowsky (2009) find that early adopters’ elections exploited SFAS No. 159’s transition guidance to manage their accounting numbers. These studies provide essentially no evidence that either early or regular adopters complied with the standard’s intent that FVO elections remedy accounting mismatches for economically offsetting positions. In contrast, we hypothesize and provide evidence that regular adopters complied with that intent, having learned from guidance the SEC and others provided about that intent and from the scrutiny early adopters’ FVO elections received. Specifically, we predict and find that variables related to accounting mismatches explain regular adopters’ FVO elections but not early adopters’ elections. We predict and find that variables related to the management of accounting and regulatory capital numbers explain early adopters’ FVO elections but not regular adopters’ elections. We also examine banks’ initial FVO elections for the three most frequently elected types of financial instruments: AFS securities and debt for early adopters and loans held for sale for regular adopters. We provide four distinct economic and accounting reasons why banks’ FVO initial elections for AFS securities and debt were both amenable to exploitation of SFAS No. 159’s transition guidance and likely to create accounting mismatches, whereas banks’ initial FVO elections for loans held for sale were both not amenable to exploitation of the standard’s transition guidance and likely to remedy accounting mismatches. Based on these reasons, we predict and find that regular adopters’ FVO elections for loans held for sale remedied accounting mismatches and did not exploit SFAS No. 159’s transition guidance. We predict and find the opposite for early adopters’ FVO elections for AFS securities and debt. Our findings are consistent with regular adopters’ FVO elections, particularly for loans held for sale, complying with SFAS No. 159’s intent. Our findings are broadly consistent with Henry’s (2009) evidence that some early adopters rescinded or revised their FVO elections because of informal mechanisms that arose to help firms interpret and implement SFAS No. 159.

Are market leaders more likely to be early adopters of business process innovations? Although they tend to enjoy economies of scale in adoption, leaders may find that adjustment costs also increase with scale. Prior work has focused on how misalignment of incumbents’ internal capabilities may affect their technology strategy. However, technology-capability misalignment may exist outside the firm boundary as well. In this paper, I build on mainstream product innovation concepts to predict when market leaders will adopt certain business process innovations. I then test these predictions in a large data set on early e-business adoption, leveraging its novel insight into focal firms, their markets, and their customers. I find market leaders were significantly more likely to embrace new information technology-enabled practices—except when customer adjustment costs were a significant concern. These findings highlight the strategic significance of external capabilities in the face of technological change. This paper was accepted by Bruno Cassiman, business strategy.

Purpose . This paper attempts to re-examine the decision of Nigeria to begin a phased adoption of International financial reporting standards from 2012.Certain emerging issues have made this important. They include researches on the effects of IFRS from the perspective of early adopters, the timeline set for adoption of IFRS by Nigeria, the current state of accounting, legal, regulatory and technological infrastructure in Nigeria and the delay by US, one of the major trading partners of Nigeria to make a firm commitment to the date of adoption. Design/Method/Approach In doing this, we rely extensively on review of theoretical and empirical literature germane to the objective of the paper.

We study the impacts of risk and ambiguity aversion on the adoption of new technologies, specifically genetically modified (GM) corn and soy seeds. We conduct experiments measuring risk and ambiguity aversion with Midwestern grain farmers. Risk aversion has only a small impact on the timing of adoption of GM soy, while ambiguity-aversion has a large impact speeding up farmer adoption of GM corn. We hypothesize that this unusual finding is due to the fact that GM corn often contains an insect-resistance trait which reduces the ambiguity of pest damages for adopters. GM soy never contains this insect-resistance trait. This highlights the importance of distinguishing between risk and ambiguity when studying the effects of aversion to uncertainty on adoption of new technologies.

We examine firm characteristics of early adoption of international financial reporting standards (IFRS) including company’s value, business complexity, corporate governance characteristics, and national levels of bureaucratic formalities in business. Because early adopters benefit from a positive network effect, they represent a driving force in harmonization and convergence. Therefore, we identify how a company’s characteristics impact its decision for early IFRS adoption. We test three groups of firms: those that adopted IFRS before the mandatory date; those that adopted IFRS on that date; and those that postponed IFRS adoption. We provide evidence, that firms’ business complexity, value, and choice of an auditor have a significant impact on early IFRS adoption. We also document that the extenuating effects of jurisdictions and national levels of bureaucratic formalities in business are factors that affect the decision to adopt IFRS.

Executive ownership guidelines are corporate polices mandating executive stock ownership in the firm. We document a dramatic increase in the adoption of executive ownership guidelines among large US firms in recent years. While early (pre-2002) adoptions appear to be driven primarily by efficient contracting between managers and shareholders, recent (post-2002) adoptions appear to be driven mainly by public pressure and firms’ herding tendency. As a result, significant post-adoption improvements in stock performance and increases in long-term investment are observed among early adopters but not among recent adopters except for a subset that is likely to have made the adoptions for efficient contracting reasons. In addition, some recent adopters exhibit abnormal increase in equity compensation that early adopters do not. These findings suggest that blind adoption of a “best practice” in corporate governance does not necessarily benefit shareholders.