Despite blockchain’s potential to transform corporations by providing new ways of organizing business processes and handling information,extant research pays inadequate attention to how and under what conditions bloc...Despite blockchain’s potential to transform corporations by providing new ways of organizing business processes and handling information,extant research pays inadequate attention to how and under what conditions blockchain technology provides additional financial value for shareholders.Drawing on the efficient market hypothesis and signaling theory,we examined the relationship between firms’blockchain use,development announcements,and stock market reactions.We used the event study methodology to analyze a sample of blockchain projects initiated by US firms between 2016 and 2019.The sample contains 114 firm-event observations.The findings show that the average abnormal return over a 2 days event period(including the day of the announcement and the day after the announcement)was positive.This positive stock market reaction is even more substantial when firms announce blockchain projects that focus on saving cost or time.Our findings also indicate that blockchain announcements tend to elicit more positive market reactions from smaller firms.We analyzed 249 firm-event observations containing firms from around the world and conclude that blockchain technology has a non-significant long-term impact on operating performance.The contingency approach adopted in our research provides advice for selecting the right mix of blockchain investment initiatives that is most suitable for a given organizational context.展开更多
Capacity planning is a very important global challenge in the face of Covid-19 pandemic.In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect,one needs to have a ...Capacity planning is a very important global challenge in the face of Covid-19 pandemic.In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect,one needs to have a good understanding of the variabilities in the demand of resources.However,Covid-19 predictive models that are widely used in capacity planning typically often predict the mean values of the demands(often through the predictions of the mean values of the confirmed cases and deaths)in both the temporal and spatial dimensions.They seldom provide trustworthy prediction or estimation of demand variabilities,and therefore,are insufficient for proper capacity planning.Motivated by the literature on variability scaling in the areas of physics and biology,we discovered that in the Covid-19 pandemic,both the confirmed cases and deaths exhibit a common variability scaling law between the average of the demand μ and its standard deviationσ,that is,σ ∝ μ^(β),where the scaling parameterμis typically in the range of 0.65 to 1,and the scaling law exists in both the temporal and spatial dimensions.Based on the mechanism of contagious diseases,we further build a stylized network model to explain the variability scaling phenomena.We finally provide simple models that may be used for capacity planning in both temporal and spatial dimensions,with only the predicted mean demand values from typical Covid-19 predictive models and the standard deviations of the demands derived from the variability scaling law.展开更多
文摘Despite blockchain’s potential to transform corporations by providing new ways of organizing business processes and handling information,extant research pays inadequate attention to how and under what conditions blockchain technology provides additional financial value for shareholders.Drawing on the efficient market hypothesis and signaling theory,we examined the relationship between firms’blockchain use,development announcements,and stock market reactions.We used the event study methodology to analyze a sample of blockchain projects initiated by US firms between 2016 and 2019.The sample contains 114 firm-event observations.The findings show that the average abnormal return over a 2 days event period(including the day of the announcement and the day after the announcement)was positive.This positive stock market reaction is even more substantial when firms announce blockchain projects that focus on saving cost or time.Our findings also indicate that blockchain announcements tend to elicit more positive market reactions from smaller firms.We analyzed 249 firm-event observations containing firms from around the world and conclude that blockchain technology has a non-significant long-term impact on operating performance.The contingency approach adopted in our research provides advice for selecting the right mix of blockchain investment initiatives that is most suitable for a given organizational context.
基金This research was supported in part by the National Natural Science Foundation of China(72042015,72091211,72031006 and 71722006).
文摘Capacity planning is a very important global challenge in the face of Covid-19 pandemic.In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect,one needs to have a good understanding of the variabilities in the demand of resources.However,Covid-19 predictive models that are widely used in capacity planning typically often predict the mean values of the demands(often through the predictions of the mean values of the confirmed cases and deaths)in both the temporal and spatial dimensions.They seldom provide trustworthy prediction or estimation of demand variabilities,and therefore,are insufficient for proper capacity planning.Motivated by the literature on variability scaling in the areas of physics and biology,we discovered that in the Covid-19 pandemic,both the confirmed cases and deaths exhibit a common variability scaling law between the average of the demand μ and its standard deviationσ,that is,σ ∝ μ^(β),where the scaling parameterμis typically in the range of 0.65 to 1,and the scaling law exists in both the temporal and spatial dimensions.Based on the mechanism of contagious diseases,we further build a stylized network model to explain the variability scaling phenomena.We finally provide simple models that may be used for capacity planning in both temporal and spatial dimensions,with only the predicted mean demand values from typical Covid-19 predictive models and the standard deviations of the demands derived from the variability scaling law.
