A tale of two clusters: knowledge and emergence

Cluster emergence is an important topic but weakly conceptualized in the literature. Focusing on the interaction of the local knowledge pool and firm growth, the paper develops a comprehensive framework to understand cluster emergence. In the framework, the cluster formation process starts with the collision of local and external knowledge which generates an innovation and stimulates the creation of local pioneering firms in a new field. To support the growth of follow-up entrants in the new industry, the local knowledge pool needs to be expanded and deepened through local knowledge sharing and external knowledge inflows. The enlarged local knowledge pool enables local firms to grow and explore other fields further. To promote cluster emergence, public policies need to facilitate the interaction of the local knowledge pool and firm growth. The paper illustrates the interactive framework with two aluminum extrusion clusters in China that emerged in different ways over different time periods.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

产业集群内生性集体行动影响因素案例研究与效度检验

基于利益集团等多重主流理论视角和半开放性编码技术的部分探索性案例研究，发现产业集群内生性集体行动受到内生需求、长期导向、本地嵌入、政策激励、同行反应、协会治理、集群规模和集群类型等因素的综合影响。经因子分析和逐步回归等方法检验，上述影响因素组合具有较为理想的建构效度和效标效度。其中，内生需求、长期导向、本地嵌入、政策激励、同行反应和协会治理等属于正面激发因素，对集群企业参与内生性集体行动具有积极促进作用，而集群规模和集群类型等则属于负面阻碍因素，对集群企业参与内生性集体行动具有消极抑制作用。     

Hotel performance: Rigor and relevant research topics

Academic research (rigor) in alignment with practitioners’ challenges (relevancy) has been advocated as a way of overcoming the ivory tower syndrome. Performance measurement is at the heart of strategic management processes, as it provides a mechanism of demonstrating outcomes. Given the importance of this topic for both theory and practice, this article explores the contribution of academic outputs in terms of academic research outputs (rigor) and current practitioners’ needs (relevancy).Using network analysis and cross-citation bibliometric approaches, a sample of 1155 articles is examined and fourteen clusters are identified. The emergent topics and subtopics from the academic literature are compared to ten insights proposed by Ernst Young to the hotel sector. The findings suggest a good fit between the two approaches together with some gaps. Based from empirical results, nine propositions are articulated.     

基于关键节点与关键路径的专利集群网络演进研究

专利作为技术和知识的重要载体，是研究技术演进和产业发展的重要信息源。目前缺乏针对专利集群网络中关键节点与关键路径中节点的比较分析和技术知识挖掘。构建基于关键节点和关键路径的专利集群网络演进模型，从两个层面综合分析技术演进特征。检索德温特数据库(Derwent Innovation Index)得到碳化硅肖特基势垒二极管（SiC-SBD）相关专利作为实证数据，时间跨度为1986-2017年。结果表明，SiC-SBD专利集群网络经历了萌芽期、成长期、成熟期和衰退期，其中，萌芽期专利主要涉及基础技术，成长期为器件结构，以完善器件结构、改进二极管性能为主要研究方向。近年来SiC-SBD专利年增长率下降，技术发展速度放缓，专利价值更多体现在其商业价值上。SiC-SBD专利集群网络关键节点与关键路径中节点重合度较高，核心专利识别可通过多视角分析得到。通过关键节点与关键路径分析专利集群网络演进过程，有助于更全面呈现技术演进过程，为决策者识别核心专利、预测技术发展提供参考。     

Logistics optimization through a social approach for food distribution

The management of supply chains is becoming more important in economic and social environments. Currently, the social sustainability is a factor that must be considered to design governmental strategies and policies. The objective of this research paper was to show, with a case study an approach to optimize distribution and delivery logistics of food in a social assistance program of school breakfast using mathematical models that include transportation distance, optimal locations, and vehicle routing through different clusters. By using qualitative variables like poverty levels, food insecurity and social exclusion, different clustering methods are proposed with the purpose of identifying the common characteristics in the studied population; and at the same time, reducing the distribution complexity. The results show an efficient approach to design a supply chain that includes economic and social factors. The new model developed in this paper can be used to plan social assistance governmental programs, to identify the specific needs and characteristics of the beneficiaries, minimizing the total cost of the distribution network logistics when delivering food for school meals.     

复杂动态环境下产业集群创新中的群体知识协同行为模型构建

在复杂动态环境下,知识协同行为（KCB）是产业集群创新（ICI）活动的有力支撑,构建复杂动态环境下产业集群创新中的群体知识协同行为模型具有重要的理论意义和实践价值。在分析复杂动态环境下产业集群创新与群体知识协同行为耦合规律的基础上,构建了复杂动态环境下产业集群创新中的群体与协同行为模型（CDE I KCBM）。与已有研究相比,该模型不仅可以反映随时间不断变化的动态演化规律,也可反映复杂动态环境下产业集群创新和群体知识协同行为的内在关联本质,有助于揭示二者的循环反馈关系。     

剥离环境因素的中国高技术产业创新效率综合测度研究

由于未剔除环境因素和随机误差的影响,运用传统数据包络分析（DEA）和随机前沿分析（SFA）对高技术产业创新效率进行研究,容易引起评价结果误差。采用二者相结合的三阶段DEA模型对高技术产业创新效率及其影响因素进行测度与分析,能够保证评价结果的有效性。研究结果显示：规模效率不足是限制我国高技术产业创新效率提升的关键因素;另外,市场开放度能够显著正向促进高技术产业创新效率提升,而政府资助、地区经济发展和地区竞争不利于创新效率提升。最后,对投入要素与技术效率进行聚类分析,将我国内地28个省市划分为4种创新类型,并〖JP〗提出提升高技术产业创新效率的政策建议。     

Personalized ads on Facebook: An effective marketing tool for online marketers

A growing number of researchers have examined the effects of personalized advertising in traditional media, however, little has been known about personalized advertising on Facebook. The primary objectives of this research are threefold: (1) Develop a comprehensive model that captures the effects of perceived personalized ads on Facebook on customer attitudinal and behavioral reactions (ad credibility, ad avoidance, ad skepticism, ad attitude, and behavioral intention) to the ad; (2) Test hypothesized relationships using two data sets collected through an online survey; and (3) Develop appropriate customer segments based on personal views of personalized ads on Facebook. The paper reveals that eleven out of thirteen hypotheses are supported and that three market segments are identified including Ad Lovers, Ad Accommodators, and Ad Haters. The paper concludes with conclusion and discussions highlighting managerial and research implications.