The quest for legitimacy and the communication of strategic cross-sectoral partnership on Facebook: A big data study

Nowadays, many wicked problems such as environmental issues require organizations from multiple sectors to form cross-sectoral alliances. Cross-sectoral alliance networks can transfer resources and signal affiliations and value alignment between strategic partners. The communication of cross-sectoral alliances is a form of CSR communication that serves organizations’ strategic goals and objectives. Drawing on the literature on digital CSR communication and legitimacy theory, this article examines which legitimacy needs shape the formation of cross-sectoral ties on Facebook in addressing environmental and sustainable development issues in the United States. Combining data-mining, text-mining, social network analysis, and exponential graph modeling, this research investigates the structure of a network among 3071 organizations across multiple sectors. Findings show that organizations’ cross-sectoral tie formation is mainly driven by social legitimacy and alliance legitimacy needs.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.     

基于信息披露文本的上市公司财务困境预测:以中文年报管理层讨论与分析为样本的研究

本文采用文本分析方法研究了中文年报管理层讨论与分析传递的管理层语调能否提供财务困境预测的增量信息、能否提高预测的准确性以及文本内容的信息价值，主要结论为：（1）管理层语调确实为财务困境预测提供了新的信息，能提高财务困境模型的拟合程度和预测能力；（2）管理层语调是对定量财务数据的重要补充，而且这些信息并没有在市场交易价格中得到充分反映；（3）负面语调比净语调具有更高的信息价值；（4）财经文本情感或语调的分析应以基于相关来源财经文本的情感词词典为基础，而直接引入其他领域成熟词典的效果较差。     

Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

‘One MBA?’ How context impacts the development of post-MBA career outcomes

Using survey data from alumni of one of the UK's earliest and largest MBA programmes we explore how career capital, career outcomes and career satisfaction are impacted by learner context. We adopt comparative capitalisms theory to investigate whether graduates from a standardised programme marketed as ‘One MBA’ report broadly similar career outcomes irrespective of their work and study location. We find that despite the rhetoric around globalisation in management education there are differences that fit the theories of comparative capitalisms literature; thus supporting the view that, despite the global nature of MBA branding, context still plays a role in shaping learning and career outcomes as evidenced by differences reported here. Significant findings are reported in terms of the reported development of career capital ‘knowing how’; career satisfaction and perceived organisational support, however differences in terms of the achievement of objective career success (promotion and career mobility) were less pronounced.     

Demographic differences in response rates for PHQ9 in a university student population

Objective: To examine differences in complete response rates for depression screening questions based on demographic characteristics. Methods: Cross-sectional study examining associations between demographic characteristics and completely responding depression-screening questions. Participants: “Healthy Minds Study” data, collected in a public University in February 2016, where 7,326 students participated. Results: women (AOR: 0.69; 95% CI =0.57–0.83) and gay/lesbian students (AOR: 0.24; 95% CI =0.10–0.60) had better complete response rates. Non-US (AOR: 1.46; 95% CI =1.03–2.07), black (AOR: 3.32; 95% CI =1.92–5.77), and Middle-Eastern students (AOR: 3.73; 95% CI =1.73–8.02) had lower complete response rates. Conclusions: Our study shows sex, gender, citizenship, and race categories have significant differences in complete response rates for the outcome. Our findings have several implications; including recognizing interventions for depression based on responders may not target those that tend to be “partial-responders”. Efforts in survey design, recruiting and completion of surveys should be maximized.     

Assessing emotional and social health using photographs: An innovative research method for rural studies and its applicability in a care-farming program for youth

A framework for assessing photographs for the emotional and social health of young people (SHAPE) is described and tested, within the context of a rural program. Two independent raters assessed the photographs of participants. To assess inter-rater reliability, Cohen’ K and Kendall’s W were calculated. The two reviewers’ assessments of photographs were in agreement. The assessment of emotional/behavioural display showed 82% agreement. Agreement between reviewers’ judgements of proxemics (W = .866), interaction (W = .722), engagement (W = .932) and overall impression (W = .804) were all significant (p < .005). The method yielded results indicating that participants found gardening immediately engaging but their approach to equines exhibited a change from fascination to confidence during the program. The visual-diary method is a useful and sensitive method for research: where resources are limited; to complement traditional measures; for use with people who lack appropriate verbal communication or literacy skills to complete questionnaires; young children; other underrepresented groups.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

全球影响力分析框架下中沙能源合作的影响因素

石油本身没有政治属性，但由石油衍生的占有权、控制权以及资源开发与利用、价格制定等因素则与国际政治经济关系密切。近年来，对外能源高依存度一直威胁着中国的能源安全并对我国经济社会发展产生着潜在的影响。沙特作为世界上石油储藏量与出口量大国之一，对满足中国能源需求意义重大。中沙具有良好的合作基础以及互补的能源战略，在能源合作方面具有广阔的前景。受国际政治经济因素的影响，中沙能源合作的主要影响因素来自美国、俄罗斯、印度和伊朗。为了保障中国的能源安全，需要进一步强化中沙能源合作力度，当前可以采取的措施主要包括：强化中沙能源领域的金融合作，建立双边制度性合作框架，协助沙特保障国家安全，与沙特和伊朗等国保持紧密的双边关系，等等。