Coping with coopetition—Facing dilemmas in cooperation for sustainable development: The case of the Dutch smart grid industry

This paper is amongst the first to examine coopetition strategy for sustainable development at the network level. Companies who want to successfully implement complex innovative technologies that support sustainable development need to collaborate with other actors of the innovation ecosystem, including their competitors, so that they can develop standards, interoperable products, pool knowledge, and resources and bundle forces to compete against other technologies. Collaboration with competitors brings benefits, but also many risks. We investigated how firms cope with these risks when establishing an innovation ecosystem to implement a new technology in society. We conducted research in the Dutch smart grids sector and explored how these firms minimize inherent risks of coopetition. We found that system‐building actors in the Dutch smart grid field not only minimize inherent risks, but from the start of their collaboration they implement so‐called enablers to prevent these risks upfront.     

Policy capturing in small‐group decision making: Using linear programming to assign factor weights for the NCAA Selection Committee's ranking decisions in the 2016 through 2018 men's basketball tournaments

We present a general approach for applying policy capturing to small‐group decision making and demonstrate the approach with the NCAA Selection Committee's rankings of the 68 teams in the three most recent Division I Men's Basketball Tournaments. We develop a linear programming model that minimizes the extent to which the evaluation of a lower‐ranked team exceeds that of a team ranked immediately above it. The result is a set of linear weights that approximates a group decision when the decision itself is demonstrably internally inconsistent in that a group ranks some teams higher than others despite a lower implied evaluation.     

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.     

Family firm’s management composition: the role played by family members’ age in TMT and supervisor levels

Quality & Quantity - Family firms (FFs) are the backbone of entrepreneurial fabric in many countries. Management of such businesses is complex because of their features: the overlap between...     

Cost comparison of continued anticoagulation with rivaroxaban versus placebo based on the 1-year EINSTEIN-Extension trial efficacy and safety results

Aims: The EINSTEIN-Extension trial (EINSTEIN-EXT) found that continued treatment with rivaroxaban for an additional 6 or 12 months (vs placebo) after 6–12 months of initial anticoagulation significantly reduced the risk of recurrent venous thromboembolism (VTE) with a small non-significant increased risk of major bleeding (none fatal or in critical site). This study aimed to compare total healthcare cost between rivaroxaban and placebo, based on the EINSTEIN-EXT event rates.

Methods: Total healthcare cost was calculated as the sum of treatment and clinical event costs from a US managed care perspective. Treatment duration and event rates were obtained from the EINSTEIN-EXT study. Adjustment on treatment duration was made by assuming a 10% non-adherence rate. Drug costs were based on wholesale acquisition costs. Cost estimates for clinical events (i.e. recurrent deep vein thrombosis [DVT], recurrent pulmonary embolism, major bleeding, clinically relevant non-major bleeding) were determined from the literature. Results were examined over a ±20% range of each cost component and over 95% confidence intervals (CIs) of event rate differences in deterministic (one-way) and probabilistic sensitivity analyses (PSA).

Results: Total healthcare cost was $1,454 lower for rivaroxaban-treated (vs placebo-treated) patients in the base-case, with a lower clinical event cost fully offsetting drug cost. The cost savings of recurrent DVT alone (–$3,102) was greater than drug cost ($2,723). Total healthcare cost remained lower for rivaroxaban in the majority (73%) of PSA (cost difference [95% CI]?=?–$1,454 [–$2,396, $1,231]).

Limitations: This study was conducted over the 1-year observation period of the EINSTEIN-EXT trial, which limited “real-world” applicability and examination of long-term economic impact. Assumptions on drug and clinical event costs were US-based and, thus, not applicable to other healthcare systems.

Conclusions: Total healthcare costs were estimated to be lower for patients continuing rivaroxaban therapy compared to those receiving placebo in VTE patients who had completed 6–12 months of VTE treatment.     

Entrepreneurship and knowledge spillovers from the public sector

A compelling body of research has found that investments in knowledge from other firms and universities spill over to enhance the performance of entrepreneurial firms. This literature has shown that firm performance is positively related to investments in new knowledge by other firms and research universities. This paper addresses a gap in the literature by positing that public sector knowledge is also conducive to enhancing performance by knowledge intensive entrepreneurial (KIE) firms. Our findings suggest that the public sector provides a fertile source of knowledge for enhancing KIE firm performance.

     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Flood Risk and Salience: New Evidence from the Sunshine State

A growing literature finds evidence that flood risk salience varies over time, spiking directly following a flood and then falling off individuals' cognitive radar in the following years. In this article, we provide new evidence of salience exploiting a hurricane cluster impacting Florida that was preceded and followed by periods of unusual calm. Utilizing residential property sales across the state from 2002 through 2012, our main estimate finds a salience impact of ?8%, on average. The salience effect persists when we base estimation only on spatial variation in prices to limit confounding from other simultaneous changes due to shifting hedonic equilibria over time. These effects range from housing prices decreases of 5.4–12.3% depending on the year of sale. Understanding flood risk salience has important implications for flood insurance and disaster policy, the benefits transfer literature, and, more broadly, our understanding of natural disaster resilience. JEL Classification: Q51, Q54, R21     

Testing the Empirical Relevance of the ‘Saving for a Rainy Day’ Hypothesis in US Metro Areas

The joint implication of the consumption Euler equation and cointegration between income and consumption is that savings predict future income declines, the ‘saving for a rainy day’ hypothesis. The empirical relevance of this hypothesis plays a key role in discussions of fiscal policy multipliers, and it holds under the null that the permanent income hypothesis is true. We find little support for this hypothesis using time series data for the 100 largest US Metropolitan Statistical Areas for the period 1980q1–2015q4. Our approach is to test for cointegration and weak exogeneity between income and consumption, and by exploring the direction of Granger causality between the two time series. We find that income more often predicts consumption and saving than the converse. We also give evidence that house price changes played a role in US income and consumption dynamics, before, during and after the Great Recession.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.