Re-internationalisation: Exploration and conceptualisation

Re-internationalisation represents a research challenge for the internationalisation process and international entrepreneurship fields. Many companies withdraw from international operations, go through an international time-out period and later re-enter the international arena. Little is known about this process, and whether re-internationalisers behave differently from those starting out for the first time. The limited, sketchy evidence is considered and it is argued that some re-internationalisers will go into the re-entry process with a significant international heritage from previous activities, including relevant knowledge and networks, enabling faster re-entry and take-off. However, other firms will have exited in such negative circumstances that international re-entry initially is rejected as an option, and may be slow to respond to new international opportunities. Much depends on what happens during the international time-out period, particularly in terms of changes in management and/or ownership; the nature and strength of new re-entry influences; and how the re-entry process unfolds.     

A neural network based dynamic forecasting model for Trend Impact Analysis

Trend Impact Analysis is a simple forecasting approach, yet powerful, within the Futures Studies paradigm. It utilizes experts' judgements to explicitly deal with unprecedented future events with varying degrees of severity in generating different possibilities (scenarios) of how the future might unfold. This is achieved by modifying a surprise-free forecast according to events' occurrences based on a Monte-Carlo simulation process. Yet, the current forecasting mechanism of TIA is static. This paper introduces a new approach for constructing TIA by using a dynamic forecasting model based on neural networks. This new approach is designed to enhance the TIA prediction process. It is expected that such a dynamic mechanism will produce more robust and reliable forecasts. Its idea is novel, beyond state of the art and its implementation is the main contribution of this paper.     

Farsightedly stable networks

A set of networks G is pairwise farsightedly stable (i) if all possible farsighted pairwise deviations from any network g G to a network outside G are deterred by the threat of ending worse off or equally well off, (ii) if there exists a farsighted improving path from any network outside the set leading to some network in the set, and (iii) if there is no proper subset of G satisfying conditions (i) and (ii). A non-empty pairwise farsightedly stable set always exists. We provide a full characterization of unique pairwise farsightedly stable sets of networks. Contrary to other pairwise concepts, pairwise farsighted stability yields a Pareto dominant network, if it exists, as the unique outcome. Finally, we study the relationship between pairwise farsighted stability and other concepts such as the largest pairwise consistent set and the von Neumann–Morgenstern pairwise farsightedly stable set.     

Comparison of customer response models

Segmentation of customers by likelihood of repeating business is a very important tool in marketing management. A number of approaches have been developed to support this activity. This article reviews basic recency, frequency, and monetary (RFM) methods on a set of data involving the sale of beef products. Variants of RFM are demonstrated. Classical data mining techniques of logistic regression, decision trees, and neural networks are also demonstrated. Results indicate a spectrum of tradeoffs. RFM methods are simpler, but less accurate. Considerations of balancing cell sizes as well as compressing data are examined. Both balancing expected cell densities as well as compressing RFM variables into a value function were found to provide more accurate models. Data mining algorithms were all found to provide a noticeable increase in predictive accuracy. Relative tradeoffs among these data mining algorithms in the context of customer segmentation are discussed.     

跨国投入产出网络中的贸易摩擦——兼析中美贸易摩擦的就业和福利效应

本文以2018年发生的中美贸易摩擦为背景,通过构建跨国投入产出网络模型刻画了关税冲击的传导机制。研究发现,关税冲击导致本国出口下降,同时加征的关税作为转移支付会提高外国的家庭收入并扩大本国消费品出口,此一负一正两种初始效应沿跨国投入产出网络向上游传导,最终形成负向的直接需求侧效应和正向的间接需求侧效应;关税冲击还通过影响相对价格增加下游行业的成本,这种效应沿跨国投入产出网络向下游传导,最终形成负向的供给侧资源再配置效应。在此基础上,本文就四轮关税加征对中美两国就业和福利的影响进行了模拟分析。结果表明,冲击在投入产出网络中的传导使得各行业关税升幅与就业损失之间存在不一致性。同时,虽然两国的总就业和福利均有所下降,但二者降幅在两国间存在非对称性,中国的福利损失高于美国,而美国就业下降的百分比高于中国。     

Exporting firm’s engagement with trade associations: Insights from Chile

This study addresses the effects of the firm’s level of engagement with trade associations located at the company’s export market on export performance. It analyzes firm-level data from a South American emerging economy, Chile. Results show that a stronger engagement with trade associations located at the company’s export market has a positive effect on export performance. Environmental uncertainty on customer needs is confirmed as an export performance barrier, but unexpectedly, this obstacle only diminishes in a negligible factor as the level of engagement with trade associations located at the firm’s export market increases. This study contributes to the international management literature by investigating the direct and moderating effects of overseas trade associations on the firm’s export performance, and by scrutinizing on the distinctions among the cooperation determinants of local networks and networks situated at the firm’s export market. Practical implications are discussed.     

我国创新网络研究演进脉络梳理及前沿热点探析

以1998-2015年CSSCI引文数据库中的创新网络文献为数据基础,运用CiteSpaceIII工具对我国创新网络研究团队、创新网络研究演进脉络以及前沿热点进行探索性分析。研究发现：我国创新网络研究有3条基本路径,并从研究背景、对象、方法、主题4个方面探讨我国创新网络研究现状。最后,分析我国创新网络研究的前沿热点问题,为未来创新网络研究奠定基础。     

核心企业伦理型领导与合作创新绩效

创新网络是企业获得外部关键性创新资源、提升竞争优势的有效平台。核心企业伦理型领导风格是影响合作创新的重要因素,探究其对合作创新绩效的影响机理具有重要意义。以社会学习、角色认知、社会交换、嵌入性等理论为基础,将心理距离纳入核心企业伦理型领导与合作创新绩效关系模型中,使用逐步回归分析法对381份有效样本进行实证分析。研究发现：道德公平、角色界定、权力分享分别对关系稳定型、合作满意型、创新能力提升型合作创新绩效有正向影响;心理距离对道德公平、角色界定与合作创新绩效的关系具有显著调节作用,但是对权力分享与合作创新绩效关系的调节作用不显著。该作用机制研究为提升合作创新绩效提供了新路径,对企业与外部组织开展合作创新活动具有重要启示。     

A relationship value perspective of social capital in networks of software SMEs

Utilizing theories on social capital, business networks, social networks and relationship value, we explore the aspects that provide specific value in relationships with different actors in the software industry. The motive for the study is the assumption that some relationships are regarded as more important than others, and companies strive to focus on fewer relationships with greater outcomes. The study is guided by the premise that social capital is a foundation for relationship value, and its identified elements differ among relationships. We take the perspective of software companies and classify their relationships with business partners into three distinctive types according to their function in the value creation process. The findings of our empirical analysis, based on a qualitative case study of eight software SMEs indicate that the aspects of social capital, like the sources of relationship value, vary systematically by the types of relationships. Thus, we are able to provide some theoretical and managerial implications on the management of small- and medium-sized companies.     

企业家社会网络对企业绩效的影响机制

本文在国内外文献就企业家的社会网络关系研究进行回顾与综述的基础上,总结了社会网络的类型及其正反两方面的影响,指出了当前许多研究片面强调企业家外部网络的作用,而忽视了内部网络。国内外研究表明,企业家社会网络对企业绩效有着正向的影响,其影响机制存在多种变量。本文根据这些研究结果,在理论上提出了企业家内、外社会网络对企业绩效影响机制的模型,并指出了其实践意义以及未来研究方向。