Dynamic Capability Building in Service Value Networks for Achieving Service Innovation

Service organizations increasingly create new service offerings that are the result of collaborative arrangements operating on a value network level. This leads to the notion of “elevated service offerings,” our definition of service innovation, implying new or enhanced service offerings that can only be eventuated as a result of partnering, and one that could not be delivered on individual organizational merits. Using empirical data from a large telecommunications company, we demonstrate through structural equation modeling (SEM) that higher‐order dynamic capabilities in services are generated as a result of collaboration between stakeholders. Furthermore, it is through collaboration and education of the stakeholders that additional higher‐order capabilities emerge (customer engagement [CuE], collaborative agility [CA], entrepreneurial alertness [EA], and collaborative innovative capacity), all of which influence the service innovation outcome. Our study also reveals empirical evidence for an ongoing process of continuous dynamic capability building in accordance with the changing dynamics of business. Managers of service organizations should recognize the potential embedded in these higher‐order skill sets, starting from collaboration, learning, and management of creative ideas for both strategic and operational benefits. Moreover, the capabilities of CA, EA, and CuE are even more important in managing the flexibility, timely delivery, and reliability of service offerings. Managers should take measures to inculcate, promote, and manage these dynamic capability skill sets to foster innovation in services.     

Semiparametric Estimators for Limited Dependent Variable (LDV) Models with Endogenous Regressors

This article reviews semiparametric estimators for limited dependent variable (LDV) models with endogenous regressors, where nonlinearity and nonseparability pose difficulties. We first introduce six main approaches in the linear equation system literature to handle endogenous regressors with linear projections: (i) ‘substitution’ replacing the endogenous regressors with their projected versions on the system exogenous regressors x, (ii) instrumental variable estimator (IVE) based on E{(error) × x} = 0, (iii) ‘model-projection’ turning the original model into a model in terms of only x-projected variables, (iv) ‘system reduced form (RF)’ finding RF parameters first and then the structural form (SF) parameters, (v) ‘artificial instrumental regressor’ using instruments as artificial regressors with zero coefficients, and (vi) ‘control function’ adding an extra term as a regressor to control for the endogeneity source. We then check if these approaches are applicable to LDV models using conditional mean/quantiles instead of linear projection. The six approaches provide a convenient forum on which semiparametric estimators in the literature can be categorized, although there are a few exceptions. The pros and cons of the approaches are discussed, and a small-scale simulation study is provided for some reviewed estimators.     

Mean-variance problem for an insurer with default risk under a jump-diffusion risk model

Abstract

This paper considers an optimal investment-reinsurance problem with default risk under the mean-variance criterion. We assume that the insurer is allowed to purchase proportional reinsurance and invest his/her surplus in a risk-free asset, a stock and a defaultable bond. The goal is to maximize the expectation and minimize the variance of the terminal wealth. We first formulate the problem to stochastic linear-quadratic (LQ) control problem with constraints. Then the optimal investment-reinsurance strategies and the corresponding value functions are obtained via the viscosity solutions of Hamilton-Jacobi-Bellman (HJB) equations for the post-default case and pre-default case, respectively. Finally, we provide numerical examples to illustrate the effects of model parameters on the optimal strategies and value functions.     

低碳技术组合应用下纵向合作减排的随机微分对策模型

在低碳电力调度准则下,基于考虑减排技术及其协同效应对低碳负荷需求的影响与电网公司购电的有限理性学习过程,建立了发电商采用3种低碳技术组合应用时的纵向合作减排的随机微分对策模型。运用汉密尔顿-雅可比-贝尔曼方程分别求得了Stackelberg博弈和合作博弈下均衡的减排技术投入、稳定的购电电量期望与方差以及Stackelberg博弈下最优的减排支付比例。考察了发电商减排技术的对称性及其应用数量对反馈均衡结果的影响,并对此两种博弈结构进行了比较分析。运用基于双向加权Rubinstein-Stahl讨价还价模型的利润共享契约使得决策系统达到协调,并将模型拓展到多种减排技术投入下的合作减排模型。研究发现:在一定条件和范围内,减排投入提高电网公司购电电量,同时发电商为此所带来的风险增大;合作博弈更适于优化电力市场电源结构,顺应低碳电力调度政策的导向;最优的减排技术应用、稳定的购电电量期望与方差以及系统均衡利润都与发电商选择的低碳技术投资效率、技术之间的协同作用以及数量正相关。     

范氏气体准静态过程的基本关系式

本文导出了v摩尔范氏气体几种常见准静态过程的基本关系式,并给予了一定的物理解释。同时又指出当a=0、b=0时,上述范氏气体关系式正好完全转变为理想气体各相应关系式。     

Heston模型下保险公司和再保险公司的投资与再保险博弈

在同时考虑保险公司和再保险公司利益的前提下,研究了保险公司和再保险公司之间的投资与再保险博弈问题。假设保险公司面临的赔付过程由带漂移的布朗运动描述。保险公司可以向再保险公司购买比例再保险,两公司均可以投资于一种无风险资产和一种价格过程服从Heston模型的风险资产,并以加权终端财富的期望效用最大化为目标,利用动态规划原理建立相应的HJB方程并求解,分别得到了保险公司与再保险公司的均衡投资与再保险策略的解析表达,并利用均衡保险市场上再保险合同的供需关系分析了保险产品的定价问题。最后通过数值实例分析了各模型参数对均衡策略的影响。     

关系学习与企业技术创新的实证研究

本研究采用问卷调研和结构方程建模方法,对企业关系学习与不同类型技术创新的关系进行了实证研究。研究关系学习分为信息分享、共同理解和关系记忆三个维度,并对关系学习和探究式创新、利用是创新的影响作用进行了分析。研究结果证实关系学习对企业的技术创新能产生积极作用。     

Estimation and Inference in Two-Step Econometric Models

A commonly used procedure in a wide class of empirical applications is to impute unobserved regressors, such as expectations, from an auxiliary econometric model. This two-step (T-S) procedure fails to account for the fact that imputed regressors are measured with sampling error, so hypothesis tests based on the estimated covariance matrix of the second-step estimator are biased, even in large samples. We present a simple yet general method of calculating asymptotically correct standard errors in T-S models. The procedure may be applied even when joint estimation methods, such as full information maximum likelihood, are inappropriate or computationally infeasible. We present two examples from recent empirical literature in which these corrections have a major impact on hypothesis testing.     

非惯性系下的两体相对运动的动力学方程及能量计算

推导、讨论了在既有平动又有转动的坐标系下的两体相对运动的动力学方程和能量方程的表达式,结果说明动力学方程和能量方程分别可视为质心系的牛顿第二定律和动能方程.通过举例说明应用.     

Sense of coherence and ill health among the unemployed and re-employed after closure of an assembly plant

The aim of this study was to investigate the relationship between employment status, ill health and sense of coherence(SOC). A cross-sectional sample of the former workers at the closed down Volvo Kalmar plant in Sweden was used. A questionnaire was mailed to all identified subjects 2 years after the closure of the plant. Responses were obtained from 344 persons, of whom 173 were re-employed and 92 were unemployed. They answered the questionnaire anonymously on background variables, SOC and ill health (physical and psychological symptoms). A notable difference was found between the re-employed and unemployed, where the unemployed reported symptoms significantly more often as well as a significantly weaker SOC. A main finding in a four cell model indicated that unemployment had a rather low impact on symptoms in the presence of a strong SOC. Structural equation modelling (SEM) was performed with simultaneous analysis of the unemployed and reemployed. The SEM analysis indicated that SOC seemed to have a greater impact on psychological symptoms among unemployed compared with re-employed persons. However, it should be noted that the present study does not allow for the determination of cause-effect relationships.