Industry 4.0 technologies in the manufacturing sector: Are we sure they are all relevant for environmental performance?

This research contributes to the debate about the relevance of Industry 4.0 technologies in improving environmental performance in the manufacturing industry. We employed a qualitative–quantitative approach in which 19 Italian operations managers were interviewed and 260 managers responded to an online questionnaire. The effects of various technologies were ranked using ordinal regression. Comments and suggestions gave context to the quantitative results. Sensors, radio-frequency identification, artificial intelligence and analytics were found to be most relevant in improving environmental performance, whereas simulation software contributed moderately. Additive manufacturing, cobots, robots, automated mobile robots and automated guided vehicles had a negative effect, augmented reality had no effect and other technologies indirectly affected environmental performance. We also found a lack of knowledge and application as well as scepticism about technologies such as artificial intelligence and augmented reality. Finally, there was concern about the disposal of electrical and electronic waste produced by these technologies.     

From private label to co-branded credit card: an assessment of the impact of a change in value proposition over customer value perception and company value capture

Journal of Financial Services Marketing - Purpose: The aim of this paper is to evaluate the success of a value proposition over time, considering two aspects: customer’s perceived value and...     

Insurance fraud detection: A statistically validated network approach

Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking on different roles. The challenge for insurance companies is to implement claim assessment and improve fraud detection accuracy. We developed an investigative system based on bipartite networks, highlighting the relationships between subjects and accidents or vehicles and accidents. We formalize filtering rules through probability models and test specific methods to assess the existence of communities in extensive networks and propose new alert metrics for suspicious structures. We apply the methodology to a real database—the Italian Antifraud Integrated Archive—and compare the results to out-of-sample fraud scams under investigation by the judicial authorities.     

Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data

Household surveys do not capture incomes at the top of the distribution well. This yields biased inequality measures. We compare the performance of the reweighting and replacing methods to address top incomes underreporting in surveys using information from tax records. The biggest challenge is that the true threshold above which underreporting occurs is unknown. Relying on simulation, we construct a hypothetical true distribution and a “distorted” distribution that mimics an underreporting pattern found in a novel linked data for Uruguay. Our simulations show that if one chooses a threshold that is not close to the true one, corrected inequality measures may be significantly biased. Interestingly, the bias using the replacing method is less sensitive to the choice of threshold. We approach the threshold selection challenge in practice using the Uruguayan linked data. Our findings are analogous to the simulation exercise. These results, however, should not be considered a general assessment of the two methods.     

CENTRAL BANK POLICIES AND INCOME AND WEALTH INEQUALITY: A SURVEY

This paper reviews recent research on the relationship between central bank policies and inequality. A new paradigm which integrates sticky‐prices, incomplete markets, and heterogeneity among households is emerging, which allows for the joint study of how inequality shapes macroeconomic aggregates and how macroeconomic shocks and policies affect inequality. The new paradigm features multiple distributional channels of monetary policy. Most empirical studies, however, analyze each potential channel of redistribution in isolation. Our review suggests that empirical research on the effects of conventional monetary policy on income and wealth inequality yields mixed findings, although there seems to be a consensus that higher inflation, at least above some threshold, increases inequality. In contrast to common wisdom, conclusions concerning the impact of unconventional monetary policies on inequality are also not clear cut. To better understand policy effects on inequality, future research should focus on the estimation of General Equilibrium models with heterogeneous agents.     

Entrepreneur subsidiary of business groups from emerging markets: a multi-level perspective

International Entrepreneurship and Management Journal - This study examines the effects of firm resources on entrepreneur subsidiaries of business groups. Resource-based theory is the foundation...     

The complementary nature of technological capabilities: Measurement and robustness issues

The application of composite indicators to complex phenomena in social science has come to remarkable prominence. As a result, they have been widely applied in wide-ranging fields. This paper explores the application of a composite indicator of technological capabilities that can be also valid for composite indicators in other fields. We focus on whether different methodologies to build composite indicators lead to different results. The arithmetic mean to aggregate technological capabilities variables has been widely criticized, as it allows for perfect substitutability between variables, thus disregarding the complementary nature of technological capabilities. We introduce a new aggregation rule, the concave mean, in order to take into account the complementarity argument in a Science-Technology-Innovation context. Using a dataset for 138 countries, we show that the arithmetic mean is biased in principle but robust in practice. This depends upon the fact that technologically more advanced countries tend to have a more complementary structure in their technological capabilities compared to less developed nations.     

The sources of use knowledge: Towards integrating the dynamics of technology use and design in the articulation of societal challenges

This paper reviews three strands of the innovation literature that have presented innovation as a distributed process that combines knowledge of designers and users: user innovations, Science and Technology Studies (STS), and domestication research. These literatures have explored different aspects of the micro-processes through which use and design knowledge are locally embedded. This paper pulls together insights from the literatures, and identifies an important gap: the connections between the local embedding of use and design knowledge, and the meso dynamics of industrial and technological change. The paper then develops a number of integrating concepts and propositions for a framework to study the co-evolution of use and design in innovation processes. It also demonstrates that this framework is most valuable in researching how societal challenges become articulated over time in processes of technological change and innovation.     

The short‐time behavior of VIX‐implied volatilities in a multifactor stochastic volatility framework

We consider a modeling setup where the volatility index (VIX) dynamics are explicitly computable as a smooth transformation of a purely diffusive, multidimensional Markov process. The framework is general enough to embed many popular stochastic volatility models. We develop closed‐form expansions and sharp error bounds for VIX futures, options, and implied volatilities. In particular, we derive exact asymptotic results for VIX‐implied volatilities, and their sensitivities, in the joint limit of short time‐to‐maturity and small log‐moneyness. The expansions obtained are explicit based on elementary functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol‐of‐vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has previously been adopted to derive approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection of model specifications.     

ARBITRAGE‐FREE BILATERAL COUNTERPARTY RISK VALUATION UNDER COLLATERALIZATION AND APPLICATION TO CREDIT DEFAULT SWAPS

We develop an arbitrage‐free valuation framework for bilateral counterparty risk, where collateral is included with possible rehypothecation. We show that the adjustment is given by the sum of two option payoff terms, where each term depends on the netted exposure, i.e., the difference between the on‐default exposure and the predefault collateral account. We then specialize our analysis to credit default swaps (CDS) as underlying portfolios, and construct a numerical scheme to evaluate the adjustment under a doubly stochastic default framework. In particular, we show that for CDS contracts a perfect collateralization cannot be achieved, even under continuous collateralization, if the reference entity’s and counterparty’s default times are dependent. The impact of rehypothecation, collateral margining frequency, and default correlation‐induced contagion is illustrated with numerical examples.