Bitcoin price and its marginal cost of production: support for a fundamental value

This study back-tests a marginal cost of production model proposed to value the digital currency Bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of production plays an important role in explaining Bitcoin prices, challenging recent allegations that Bitcoins are essentially worthless. Even with markets pricing Bitcoin in the thousands of dollars each, the valuation model seems robust. The data show that a price bubble that began in the Fall of 2017 resolved itself in early 2018, converging with the marginal cost model. This suggests that while bubbles may appear in the Bitcoin market, prices will tend to this bound and not collapse to zero.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

International trade of GMO-related agricultural products

This paper examines the international trade of a variety of genetically modified (GM) food products over a 27-year period (1984–2011) with data from the United Nations using the tools of social network analysis. The results indicate that each of the different crops have a distinctive pattern of trade that has changed over time due to a number of different factors. Also, trade in agricultural commodities became more diversified over time, dominated less by the United States and other nations central in the trade networks and trade in the individual GM crops was stable over time. Countries maintained their trading partners for specific crops, despite the adoption of the genetically modified varieties. The economic implications of these results are discussed for specific countries.     

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

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

Multi-level and mixed-level <Emphasis Type="Italic">k</Emphasis>-circulant supersaturated designs

Supersaturated designs (SSDs) constitute an important class of fractional factorial designs that could be extremely useful in factor screening experiments. Most of the existing studies have focused on balanced designs. This paper provides a new lower bound for the \(E(f_{NOD})\)-optimality measure of SSDs with general run sizes. This bound is a generalization of existing bounds since it is applicable to both balanced and unbalanced designs. Optimal multi and mixed-level, balanced and nearly balanced SSDs are constructed by applying a k-circulant type methodology. Necessary and sufficient conditions are introduced for the generator vectors, in order to pre-ensure the optimality of the constructed k-circulant SSDs. The provided lower bounds were used to measure the efficiency of the generated designs. The presented methodology leads to a number of new families of improved SSDs, providing tools for directly constructing optimal or nearly-optimal k-circulant designs by just checking the corresponding generator vector.     

Reciprocal value sharing in manufacturer-retailer relationships: the case of new product introductions

Prior literature examined reciprocity in the context of value creation. However, research has yet to examine whether reciprocity exists in value sharing. To address this gap, the authors examine retailer’s reciprocal value sharing with its manufacturer in relation to new product introductions. The authors test, via a survey of retail managers, whether reciprocal value sharing is influenced by an interaction of manufacturer’s prior new product success with innovativeness of a manufacturer’s products and the frequency of new product introduction. The results indicate that a retailer’s reciprocal value sharing is greater when the manufacturer historically launched successful new products, and that this effect is decreased with the innovativeness of a manufacturer’s products but increased with the frequency of new product introduction.     

Gamified interactions: whether,when, and how games facilitate self–brand connections

Firms increasingly use games to interact with their customers. Yet, surprisingly little is known about whether, when, and how such “gamified” interactions engage consumers with a firm’s brand, thereby facilitating self–brand connections. Building on flow theory, we show that gamified interactions that are highly interactive and optimally challenging facilitate self–brand connections, because such games lead to emotional and cognitive brand engagement. A field study and three experiments across various product domains and game designs support our theory. We also identify conditions under which consumers do not become engaged with a brand, namely when firms restrict their decisional control either to voluntarily participate in the game (i.e., compulsory play) or to spend as much time as desired playing the game (i.e., time pressure). Our findings advance existing knowledge about the use of games in marketing and provide important implications for how marketers can harness their potential to build self–brand connections.     

Human resource management practices and voluntary turnover: a study of internal workforce and external labor market contingencies

We tested relationships between employee quit rates and two bundles of human resource (HR) practices that reflect the different interests of the two parties involved in the employment relationship. To understand the boundary conditions for these effects, we examined an external contingency proposed to influence the exchange-based effects of HR practices on subsequent quit rates – the local industry-specific unemployment rate – and an internal contingency proposed to shape employees’ conceptualization of their exchange relationship – their employment status (i.e. full-time, part-time and temporary employment). Analyses of lagged data from over 200 Canadian establishments show that inducement HR practices (e.g. extensive benefits) and performance expectation HR practices (e.g. performance-based bonuses) had different effects on quit rates, and the former effect was moderated by unemployment rate. The effects of HR practices on quit rates did not differ between FT and PT employees, but a different pattern of main and interactive effects was found among temporary workers. These findings suggest that employees’ exchange-based decisions to leave may be less affected by the number of hours they expect to work each week, and more by the number of weeks they expect to work.