The role of leadership in shared value creation from the public’s perspective: A multi-continental study

Porter and Kramer’s concept of creating shared value (CSV) has been welcomed as an approach to corporate social responsibility (CSR) among corporations that also provides a practical opportunity for dialogue in public relations, but it has been little examined from the general population’s (i.e., the public’s) perspective. Such scrutiny is important because its findings enable public relations to contribute to the debate and development of CSV from both the public’s and the organization’s viewpoints. Additionally, if public relations professionals understand how the public perceives CSV, they can give a strategic perspective to top management for maximizing moral capabilities of the business and formulate effective communication to promote CSV initiatives. This study investigates whether the public prefers corporations to practice CSV as opposed to intrinsic CSR as a separate pursuit from business interests. It also explores the role of leadership as an influential and ethical construct in implementing effective CSV as perceived by the public. The public’s preference for CSV over intrinsic CSR was revealed in a survey of 1784 participants in the United States (US), Germany, and China. Factor analysis results further suggested that effective CSV competencies of CEOs were construed as a unidimensional concept in the US, but German and Chinese participants viewed it as two-dimensional. The public perceived that leaders’ moral character played a more important, core role in effective CSV than did altruistic and behavioral attributes, across nations. Network analysis of the perceived effective CSV-characteristics provides further implications for CSV communication.     

Career Decision State and Assessment of RIASEC Interest Structure

The career decision state (CDS) was studied in relation to RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, Conventional) profiles in Self-Directed Search results among college students (86 women, 27 men). Three CDS dimensions measured by the Career State Inventory (CSI; certainty, satisfaction, and clarity) were examined as predictors of RIASEC primary and secondary constructs. Significant, albeit modest, zero-order correlations (p < .05) emerged between clarity and 3 secondary constructs (i.e., consistency, commonness, and coherence). Results of regression analyses indicated that CSI dimensions predicted 1 secondary construct (i.e., commonness).     

属性集容量确定的夹挤式测度模式及其推算模型

迄今，为解决多属性偏好关联决策属性集容量判断指数复杂性难题所提出的λ模糊测度模式与k-可加模糊测度模式，以及建构在它们之上的属性集容量确定的推算模型，尚存在着适用性差的技术不足。为此，以平衡容量判断的可操作性和容量推算的准确性为视角，提出了一种新容量测度模式，即关于容量判断与推算的夹挤式测度模式，并在此基础上通过引入决策者较易判断给出的容量序信息构建了相应的容量推算模型。基于数值模拟的对比分析表明：新模式不仅在应用可行性上高于k-可加模糊测度模式，而且从容量推算的准确性上看也明显优于λ模糊测度模式和k-可加模糊测度模式，因而对实际决策具有更强的适用性。     

考虑消费者双重偏好的低碳供应链减排策略研究

为了削弱传统零售商在渠道博弈中的垄断地位，制造商尝试建立在线渠道与零售商展开竞争。本文在考虑消费者低碳偏好的基础上，又将消费者的渠道偏好进行区分，通过不同决策模式的对比及数值算例分析，寻求低碳供应链最优的减排边界。研究表明：1分散决策时，制造商的低碳决策会受消费者渠道偏好的影响；集中决策时，制造商的低碳决策保持不变。2不同决策模式的减排边界由渠道偏好决定，渠道偏好较大时，分散决策的减排边界更高；渠道偏好较低时，集中决策的减排边界更高；渠道偏好中立时，两者的减排边界相同。3制造商可以通过升级低碳技术、实行低碳化管理等方式降低减排成本，同时通过低碳产品认证、广告宣传等方式提高消费者对低碳产品的认可程度。     

Does Joint Physical Custody “Cause” Children’s Better Outcomes?

ABSTRACT

Policymakers and researchers are concerned with whether joint physical custody (JPC) produces better outcomes for children than sole custody. Although several review articles summarizing up to 61 empirical articles demonstrate very positive answers, many of the research designs used compromise the ability to claim that it is JPC per se—and not selection effects—that causes the effect. We discuss several research design issues, such as propensity score analysis, that can more powerfully probe the question of causality. Some studies have already been conducted employing these strategies and more are recommended and likely to soon be forthcoming. On the basis of this comprehensive review we conclude that JPC probably does cause benefits to children on average, and that social scientists can now provisionally recommend rebuttably presumptive JPC to policymakers.     

Children in immediate danger: Emergency removals in Finnish and Irish child protection

This paper presents a qualitative analysis of front‐line practices regarding emergency removals in Finnish and Irish child protection. It examines how the responses to children's immediate danger are framed by legislation and how front‐line practitioners assess the child's situation and make emergency placement decisions. The data consist of interviews with 16 Irish and 33 Finnish social workers. These child welfare protection systems respond differently to a task that appears to be similar. The Irish team‐based practice rests on the social workers' shared assessment of the child's needs, and the formal decision is made by the courts (or police officers at night‐time); and the Finnish practice involves only one single social worker who makes both the assessment and the removal decision. The Irish system is tightly time regulated, whereas the Finnish system provides a more flexible time frame. Both approaches put a lot of stress on social workers' practice, which also includes creative workarounds (e.g., “planned emergency removals” in Finland). Future research will need to explore these features from the point of view of a child's right to protection.     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions

Achieving health gains from the U.N. Sustainable Development Goals of universal coverage for water and sanitation will require interventions that can be widely adopted and maintained. Effectiveness—how an intervention performs based on actual use—as opposed to efficacy will therefore be central to evaluations of new and existing interventions. Incomplete compliance—when people do not always use the intervention and are therefore exposed to contamination—is thought to be responsible for the lower‐than‐expected risk reductions observed from water, sanitation, and hygiene interventions based on their efficacy at removing pathogens. We explicitly incorporated decision theory into a quantitative microbial risk assessment model. Specifically, we assume that the usability of household water treatment (HWT) devices (filters and chlorine) decreases as they become more efficacious due to issues such as taste or flow rates. Simulations were run to examine the tradeoff between device efficacy and usability. For most situations, HWT interventions that trade lower efficacy (i.e., remove less pathogens) for higher compliance (i.e., better usability) contribute substantial reductions in diarrheal disease risk compared to devices meeting current World Health Organization efficacy guidelines. Recommendations that take into account both the behavioral and microbiological properties of treatment devices are likely to be more effective at reducing the burden of diarrheal disease than current standards that only consider efficacy.     

The Career Decision‐Making Difficulties Questionnaire: A Case for Item‐Level Interpretation

The Career Decision‐Making Difficulties Questionnaire (CDDQ; Gati, Krausz, & Osipow, 1996) has long been demonstrated as a useful instrument for career counseling practice. Several case studies have demonstrated how and why using the CDDQ facilitates the career counseling process (e.g., Amir, Gati, & Kleiman, 2008; Gati & Levin, 2014; Levin & Gati, 2014). This study explores how an in‐depth analysis of a case study conducted at the item level can provide career counselors with a richer understanding of their clients’ needs. The case study also emphasizes how administering and providing feedback on the CDDQ in career counseling sessions is likely to foster working alliances. The study concludes by presenting an intervention map based on the CDDQ taxonomy.     

基于混合加权距离的毕达哥拉斯模糊TOPSIS多属性决策方法研究

针对决策信息为毕达哥拉斯模糊集的多属性决策问题，提出了一种基于混合加权测度的TOPSIS决策方法。在分析了现有距离测度方法不足的基础上，首先给出了一种新的毕达哥拉斯模糊距离测度——毕达哥拉斯模糊有序加权距离（PFOWD），并研究了该测度权重的确定方法；在PFOWD基础上，进一步提出了毕达哥拉斯模糊混合加权距离（PFHWD），同时探讨了其特征和与现有毕达哥拉斯模糊测度的关系；最后提出了一种基于PFHWD测度的毕达哥拉斯模糊TOPSIS多属性方法，并用实例验证了方法的有效性和可行性。