Measuring servitization progress and outcome: the case of ‘advanced services’

The purpose of this paper is to establish a framework for assessing the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’ – a complex bundling of products and services, whereby manufacturers offer capabilities and outcomes instead of products alone. ‘Advanced services’ represent the most complex offering in the current servitization trend amongst manufacturers. However, current performance measures lack the breadth and focus to assess progress or outcomes, and so support research and practice of organisational transformation efforts required. To address this gap the paper investigates how a manufacturer’s efforts to become an ‘advanced services’ provider can be comprehensively measured, and develops a framework for assessing the transformation journey towards becoming an ‘advanced services’ provider. The research method is based on (1) a systematic literature review process to create a comprehensive set of service-related performance measures that are available to assess a manufacturer’s servitization efforts, followed by (2) an engagement with an expert panel to synthesise the identified measures and create a set of ‘advanced services’ performance measures. The proposed framework is presented as a scorecard that can be used in practice to assess the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’.     

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。     

Global product development projects: measuring performance and monitoring the risks

Abstract

This article investigates the development and application of key performance indicators for global product development. Two in-depth, longitudinal case studies with multinational Danish manufacturing companies were conducted, and highlight how key performance indicators, typically used for collocated, cross-functional product development, do not provide the predictive insight required to avoid the additional risks encountered in the global product development environment. Grounded in the case study results and building on established methodologies in performance measurement literature, a framework was developed and validated in two additional Danish companies to support project managers to develop: preventive indicators, which support the avoidance of identified risks, and outcome indicators, which support the measurement towards the attainment of project objectives. The study is unique as it is one of the very few longitudinal studies of engineering design activities in a global context, providing the in-depth contextual understanding towards key risks and their influence on performance; an important step to support researchers and practitioners with the development of preventive measures.     

Probabilistic frontier regression models for binary type output data

This paper proposes a probabilistic frontier regression model for binary type output data in a production process setup. We consider one of the two categories of outputs as ‘selected’ category and the reduction in probability of falling in this category is attributed to the reduction in technical efficiency (TE) of the decision-making unit. An efficiency measure is proposed to determine the deviations of individual units from the probabilistic frontier. Simulation results show that the average estimated TE component is close to its true value. An application of the proposed method to the data related to the Indian public sector banking system is provided where the output variable is the indicator of level of non-performing assets. Individual TE is obtained for each of the banks under consideration. Among the public sector banks, Andhra bank is found to be the most efficient, whereas the United Bank of India is the least.     

Estimating the population proportion in modified ranked set sampling methods

In this paper, proportion estimators and associated variance estimators are proposed for a binary variable with a concomitant variable based on modified ranked set sampling methods, which are extreme ranked set sampling (ERSS), median ranked set sampling (MRSS), percentile ranked set sampling (Per-RSS) and L ranked set sampling (LRSS) methods. The Monte Carlo simulation study is performed to compare the performance of the estimators based on bias, mean squared error, and relative efficiency for different levels of correlation coefficient, set and cycle sizes under normal and log-normal distributions. Moreover, the study is supported with real data application.     

Oracle GMM estimation for misspecified models via thresholding

We propose a thresholding generalized method of moments (GMM) estimator for misspecified time series moment condition models. This estimator has the following oracle property: its asymptotic behavior is the same as of any efficient GMM estimator obtained under the a priori information that the true model were known. We propose data adaptive selection methods for thresholding parameter using multiple testing procedures. We determine the limiting null distributions of classical parameter tests and show the consistency of the corresponding block-bootstrap tests used in conjunction with thresholding GMM inference. We present the results of a simulation study for a misspecified instrumental variable regression model and for a vector autoregressive model with measurement error. We illustrate an application of the proposed methodology to data analysis of a real-world dataset.     

An improved cluster two-stage randomized response model

In this paper, Abdelfatah and Mazloum's (2015) two-stage randomized response model is extended to unequal probability sampling and stratified unequal probability sampling, both with and without replacement. The extended models result in more efficient estimators than Lee et al.'s (2014) estimators of the proportion of the population having a sensitive attribute.     

微信公众号影响力指数建构与量化评估

作为被广泛使用的社交媒体，微信已经成为热点事件和网络舆情的重要策源地，科学准确评估微信公众号的影响力对于明晰微信信息传播特点，深入挖掘微信传播潜力，进一步规范和指导微信平台的传播行为具有较大的理论和实践意义。在对既有关于微信公众号影响力研究进行梳理和评价的基础上，基于传播效果测量的设计，坚持以受众为中心、由浅入深多层次考察准则，运用德尔菲法和层次分析法建构一套微信公众号影响力指标体系。该指标体系由4个一级指标和9个二级指标构成，并运用线性合成法合成微信公众号影响力指数。     

治理效能视角下公民参与公共服务的制度研究

公民参与公共服务的有序性和有效性并非直接相关,可以从有序性和有效性两个维度分析公民参与及其治理效能的关系.为提升治理效能,以程序性规则为核心的制度设计能更为充分地保障公民有序有效参与公共服务,实现公民与政府之间的良性互动与有序合作.基于全过程民主、程序性权利和共同体秩序等公民参与的程序性价值维度考量,再以环境保护领域中的公民参与为例,从公开公示机制、意见表达机制、回应吸纳机制、监督评价机制和责任追究机制等方面构建公民全过程参与制度,并探索公民参与的方法和策略.通过公民参与的程序性价值内化、方法创新与技术转型来推进治理体系和治理能力现代化.     

Developing a Broadly Applicable Measure of Risk Perception

Decades of research identify risk perception as a largely intuitive and affective construct, in contrast to the more deliberative assessments of probability and consequences that form the foundation of risk assessment. However, a review of the literature reveals that many of the risk perception measures employed in survey research with human subjects are either generic in nature, not capturing any particular affective, probabilistic, or consequential dimension of risk; or focused solely on judgments of probability. The goal of this research was to assess a multidimensional measure of risk perception across multiple hazards to identify a measure that will be broadly useful for assessing perceived risk moving forward. Our results support the idea of risk perception being multidimensional, but largely a function of individual affective reactions to the hazard. We also find that our measure of risk perception holds across multiple types of hazards, ranging from those that are behavioral in nature (e.g., health and safety behaviors), to those that are technological (e.g., pollution), or natural (e.g., extreme weather). We suggest that a general, unidimensional measure of risk may accurately capture one's perception of the severity of the consequences, and the discrete emotions that are felt in response to those potential consequences. However, such a measure is not likely to capture the perceived probability of experiencing the outcomes, nor will it be as useful at understanding one's motivation to take mitigation action.