Achieving new product success via the synchronization of exploration and exploitation across multiple levels and functional areas

While ambidexterity has been identified as a critical prerequisite for new product success, synchronizing exploration and exploitation in practice represents a multifaceted enigma. Ambidexterity is not in reality limited to a single organizational level, or a specific functional area. Firms become ambidextrous when corporate-level exploratory and exploitative strategies interact with operational-level exploratory and exploitative capabilities across multiple functional areas. Data from a sample of technology-intensive industrial firms using a multi-informant design shows that operational-level exploratory and exploitative product innovation and marketing capabilities allow firms to implement corporate-level exploratory and exploitative strategies in the context of new product development (NPD). Further, the findings reveal that the integration of exploratory product innovation–exploratory marketing and exploitative product innovation–exploitative marketing is significant for the implementation of exploratory and exploitative strategies over deploying each capability in isolation. Finally, we show that the implementation of exploratory and exploitative strategies drives new product success through creating distinct positional advantages to customers in the form of both differentiation and cost efficiency. These positional advantages help to better explain the effects of exploratory and exploitative capabilities on new product market performance.     

Composing tweets to increase retweets

Brands tweet not only to communicate with followers but also to reach large audiences rapidly when the tweets are retweeted by the followers. People however will retweet only if they recognize within a few seconds that the tweet is on an interesting topic. Brands therefore need insights into how to compose tweets to facilitate topic recognition even when they are just scanned. This is the issue that we address in this research. Specifically, drawing on findings in psycholinguistics, we empirically investigate if tweets composed such that they include more topic-related words that are located closer to the start get more retweets. Results from an investigation of sales-promotional tweets by sixty brands in four categories indicate that tweets that are composed as above do get more retweets. We repeat the investigation using tweets on several other topics from a natural experiment that generated pairs of tweets where each pair is on the same topic but each tweet in the pair is composed differently. This investigation reconfirms the findings from the analysis of retweets of sales-promotional tweets. We conclude by presenting an approach for how social media managers can compose tweets based on our findings.     

Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems

In this paper, an integrated mathematical model of the multi-period cell formation and production planning in a dynamic cellular manufacturing system (DCMS) is proposed with the aim of minimizing machine, inter/intra-cell movement, reconfiguration, partial subcontracting, and inventory carrying costs. This paper puts emphasis on the effect of the trade-off between production and outsourcing costs on the re-configuration of the cells in cellular manufacturing systems (CMSs) under a dynamic environment, in which the product mix is different from a period to another resulting in the operational dynamism in the cells. The proposed model is verified by a number of numerical examples and related sensitivity analysis.     

Forecasting With the Standardized Self‐Perturbed Kalman Filter

We propose and study the finite‐sample properties of a modified version of the self‐perturbed Kalman filter of Park and Jun (Electronics Letters 1992; 28 : 558–559) for the online estimation of models subject to parameter instability. The perturbation term in the updating equation of the state covariance matrix is weighted by the estimate of the measurement error variance. This avoids the calibration of a design parameter as the perturbation term is scaled by the amount of uncertainty in the data. It is shown by Monte Carlo simulations that this perturbation method is associated with a good tracking of the dynamics of the parameters compared to other online algorithms and to classical and Bayesian methods. The standardized self‐perturbed Kalman filter is adopted to forecast the equity premium on the S&P 500 index under several model specifications, and determines the extent to which realized variance can be used to predict excess returns. Copyright © 2016 John Wiley & Sons, Ltd.     

Research Forecasting for Health Information Technology (HIT), using technology intelligence

Due to the rapid pace of change in technology and its impact on society, there is an increasing demand for use of Technology Forecasting methods to improve policy planning and implementation. One such area is the field of Health Care and the impact of Health Information Technology (HIT) on this field. Using HIT has shown to be associated with reduced cost, improved quality, and better patient experience; yet HIT adoption has been slow. Therefore, there is a need to better understand the HIT adoption processes in order to meet the evolving requirements for health care delivery.We propose collecting Technology Intelligence for use in Research Forecasting as part of the larger HIT Technology Forecasting efforts. In this study, we systematically probed for HIT-related technology intelligence in the fields of Information Systems, Engineering Management, and Medical Informatics. Results of our analysis show that all three fields are active in Health IT research, but could benefit from further collaboration. We were also able to identify instances of emerging journals and emerging topics in Health IT research. We conclude that it is indeed plausible and meaningful to collect technology intelligence on HIT adoption, to support the overall goal of improving healthcare delivery.     

Crude oil price volatility dynamics and the great recession

Using a very simple econometric framework, we identify two major changes in the dynamics of crude oil price volatility based on data from 1997 to 2017. More precisely, we model weekly West Texas Intermediate (WTI) crude oil price realized volatility in a two-regime setting, one where realized volatility evolves as a plain autoregressive (AR) process (static), and the other where the level, persistence and innovation volatility of the AR process are subject to changes (dynamic). We use a Markov chain to model the probability that the process is in the static regime. The post Great Recession period sees a longer duration of the dynamic regime as well as smaller changes in the level and conditional volatility of realized volatility when switching actually occurs. Crude oil volatility also responds more aggressively to changes in economic variables, such as the t-bill rate and equity market volatility in the dynamic regime.     

Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?

We study to what extent the financial crisis of 2008 and its aftermath have changed the impact of inflation on inflation uncertainty in the 12 original member states of the European Monetary Union (EMU). We adopt a time‐varying coefficient regression model with stochastic volatility effects, and extract two measures of inflation uncertainty from our data, namely, (1) The conditional volatility of inflation, (2) The conditional volatility of steady‐state inflation. (1)–(2) represent short‐run and steady‐state inflation uncertainty, respectively. The time‐varying impact of inflation on inflation uncertainty is analyzed using Markov‐switching regressions, where switching between the low and high inflation uncertainty regime is determined via an unobserved Markov process. Results suggest that the 2008 financial crisis and its aftermath have changed the impact of inflation on (1) and (2) across the selected EMU member states. However, a uniform pattern cannot be detected. For some member states, we document a strong link, whereas for others, the impact of inflation on inflation uncertainty is relatively weaker.     

Supporting new product commercialization through managerial social ties and market knowledge development in an emerging economy

While it has been advocated that the generation and application of market knowledge shape marketing capabilities to commercialize new products, the weak institutional environment makes access to critical market knowledge challenging in emerging economies. Critically, managerial social ties with business and political institutions may complement the firm’s market orientation (MO) to obtain market knowledge that is not available in the open market in emerging economies. This study draws attention to the differential roles of business and political ties in complementing or inhibiting the effects of market orientation on exploratory and exploitative marketing capabilities in one of the “Next Eleven” emerging economies, Iran. The results help firms operating in emerging economies to identify the conditions under which business and political ties help to overcome institutional limitations, complement market-oriented efforts, and successfully commercialize new products.     

Oil jump risk

The risk premium associated with large upside jumps in oil market is a significant driver of the cross-section of stock returns from 1986 to 2014. In contrast to previous research, variance risk is priced only when we do not control for jumps. Upward jumps are priced in tight supply-demand conditions but not in more abundant supply periods. There is some evidence that downward jumps are priced in abundant supply conditions but not in tight conditions. Innovations in risk neutral jumps have predictive power for important economic indicators, including notably consumption growth. This helps explain the pricing of jump risks.