Avoiding digitalization traps: Tools for top managers

Digital transformation is fundamentally changing the business landscape. It is also affecting the roles of top managers within firms. Our survey of more than 160 senior managers in Europe suggests that digitalization, rather than encouraging more decentralized forms of management, will lead to an expanded role for headquarters and further empowerment of top managers. While acknowledging the benefits of the digital transformation, in this Executive Digest we identify five key challenges for newly empowered top managers and offer solutions for these digitalization traps.     

创业失败经验对连续创业意愿的影响——创业失败学习与市场动荡性的作用

基于经验学习理论，探究创业失败经验如何通过创业失败学习影响创业者连续创业意愿，以及市场动荡性的调节作用。对176位有失败经历的创业者进行问卷调查，结果表明：创业失败经验对创业失败学习和连续创业意愿均有显著正向影响；创业失败学习在创业失败经验与连续创业意愿关系间起中介作用；市场动荡性负向调节创业失败学习与连续创业意愿的关系，即市场动荡性越高，创业失败学习与连续创业意愿间的关系越弱。研究结论对于拓展创业失败经验与连续创业意愿研究、帮助创业者从失败中复原，以及激励连续创业具有重要理论价值和实践意义。     

An analytical model proposal to design urban open spaces in balance with climate: A case study of Gaziantep

A significant decline has been experienced in the quality of life of people living in cities due to the deterioration of the ecological balance, decrease in biodiversity, together with air, noise and water pollution occurring as a result of population growth and urbanization. All of these factors have triggered global warming, which is one of the biggest problems in recent years. For this reason, the climate has become one of the most important factors in urban design works. The purpose of the present study is to determine the microclimatic contribution of urban open spaces to the city in the context of climate-balanced physical planning criteria, and to propose an analytical model, which may constitute a basis for planning and design works. Firstly, the climatic requirements of the city of Gaziantep were examined by creating bioclimatic comfort maps. In the following stage, monthly wind roses were created by determining the dominant wind directions for the summer and winter seasons. Optimum location and directions that were balanced with climate were determined and slope and aspect maps of the area, land use types and area selection criteria were also created. In light of these data, ecological compatibility and feasibility maps were prepared. In the feasibility map, the temperature and humidity maps were created with ENVI-met, which is a climatic simulation software, for the most extreme days in an area where there were residential areas and educational institutions, multi-storey residential areas, working areas, social and open green areas, and afforestation areas. The results that were obtained with the simulations were subjected to Regression Analysis to determine the relationship among the climate parameters and the design criteria. As a result, the increase in the quantity of urban green spaces and equality on the spatial distribution of these areas will improve bioclimatic comfort (the warmest hour of the hottest period regression analysis’ result is β= -0.384). It has been determined that planning high-density plantation in green spaces and selecting dense and broad-leaved plants will provide a cooling effect (on average 2−3 °C less). Furthermore, adding more green spaces in cities will increase the thermal comfort within city blocks, especially where high-rise buildings are common. It is confirmed that high-rise buildings cause thermal stress (the warmest hour of the hottest period regression analysis’ result is β = 0.472). Hardscapes have a negative effect on the temperature (the warmest hour of the hottest period regression analysis’ result is β = 0.425). In addition to these data, it was found that the mean radiant temperature values, instead of temperature values, would yield more accurate results in microclimate analyses and interpretations.     

The use of landslide hazard maps to determine mitigation priorities in a dam reservoir and its protection area

Despite longstanding research on the landslide hazard assessment and mapping, the use this information in regional planning applications remains largely unclear. There is still a need for novel methods to interpret the results of hazard analyses. In this respect, the main research question of this study is how the landslide hazard maps can be evaluated in planning practice. To evaluate this issue, a comprehensive case study was carried out and a new methodology, defining the order of priority for the locations where mitigation measures are applied was developed. The investigations were carried out in the Melen Dam reservoir, which provides potable water to the city of Istanbul, and the dam protection area (Duzce, Turkey) in four main stages: (i) Evaluation of the general characteristics of the study area, (ii) preparation of landslide inventory, (iii) development of landslide hazard model, and (iv) implementation of the results of hazard analyses in planning. As a consequence, a decision support system that can evaluate analytically complicated outputs “P_Combined”, “P_{AL min.}”, and “L_Total” and provide clear decisions “Urgent”, “Primary”, and “Secondary” was suggested. Considering the limited resources available for the mitigation measures, the determination of mitigation priorities for the micro-catchments constitutes the key land-use policy for the protection of the dam reservoir.     

Environmental Outcomes of Urban Land System Change: Comparing Riparian Design Approaches in the Phoenix Metropolitan Area

In the face of climate change and other environmental challenges, an increasing number of cities are turning to land design to enhance urban sustainability. Land system architecture (LSA)—which examines the role of size, shape, distribution, and connectivity of land units in relation to the system’s social-environmental dynamics—can be a useful perspective for examining how land contributes to the social and environmental aspects of urban sustainability. There are two gaps, however, that prevent LSA from fully contributing to urban sustainability dialogues. First, it is not well understood how urban design goals, as expressed by urban planners and other practitioners, relate to LSA and environmental outcomes. Second, most LSA work focuses on individual environmental outcomes, such as the urban heat island effect, instead of considering the broader suite of outcomes that LSA changes impact. Here, we undertake an integrated assessment of LSA impacts on surface urban heat island (based on land surface temperature), vegetation presence/health (based on NDVI), and bird biota at two riparian sites with different design intentions in the Phoenix, Arizona metropolitan area. The Rio Salado in Tempe underwent a city-led, infill redevelopment that mixed economic, recreational, and flood control design goals. The New River in Peoria experienced a more typical developer-driven urbanization. The contexts and design goals of the sites generated differences in their LSA, but only a few of these differences were sufficiently unique to contribute to divergent environmental outcomes. These differences reside in (1) the greater distribution of recreational land-covers and (2) increased surface water at the Rio Salado site compared to the New River site. Both changes are linked to land-cover patches becoming greener and cooler as well as a greater presence of waterbird and warbler species at the Rio Salado site. The distinctions between the sites provide insight for crafting design goals for redeveloping or restoring urban riparian landscapes in the Phoenix metropolitan area that are grounded in LSA. With the incorporation of additional relevant variables, especially socioeconomic ones, the research approach employed in this study provides a foundation for the assessment of other urban land system change.     

Correlated daily time series and forecasting in the M4 competition

We participated in the M4 competition for time series forecasting and here describe our methods for forecasting daily time series. We used an ensemble of five statistical forecasting methods and a method that we refer to as the correlator. Our retrospective analysis using the ground truth values published by the M4 organisers after the competition demonstrates that the correlator was responsible for most of our gains over the naïve constant forecasting method. We identify data leakage as one reason for its success, due partly to test data selected from different time intervals, and partly to quality issues with the original time series. We suggest that future forecasting competitions should provide actual dates for the time series so that some of these leakages could be avoided by participants.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

Geographies of Algorithmic Violence: Redlining the Smart City

City governments are embracing data-driven and algorithmic planning to tackle urban problems. Data-driven analytics have an unprecedented capacity to call urban futures into being. At the same time, they can depoliticize planning decisions. I argue that this shift calls urban studies scholars to investigate geographies of algorithmic violence—a repetitive and standardized form of violence that contributes to the racialization of space and spatialization of poverty. This article examines this broader phenomenon through the case of a proprietary market value assessment that is being used to guide development in cities across the United States. The assessment employs an algorithm that helps city officials make critical decisions about which neighborhoods to target for investment, disinvestment and public service upgrades or disconnections. I argue that the racial, infrastructural, and epistemological violence associated with this evaluation can potentially lead to a new kind of municipal redlining. The article brings insights from critical race theory into conversation with critical scholarship on algorithms by analyzing how algorithmic violence works through data-driven planning technologies to depoliticize and leverage power while further entrenching racism and inequality.