Diversified behavioral portfolio as an alternative to Modern Portfolio Theory

The traditional mean–variance approach has been complemented by alternative theories that use risk measures different from standard deviation of returns or involve additional distributional features of returns like skewness and kurtosis. We propose a portfolio choice model that combines different distributional characteristics of the returns in the decision-making making process, considering preferences of investors which are modeled as non-statistical uncertainties of investors using fuzzy theory. We use 20 stocks of the S&P500 from January 2013 to December 2017. We assess the obtained portfolios’ performance, and the diversified behavioral portfolios outperform than the mean–variance portfolio. This methodological proposal can be seen as a strong managerial tool to make investment portfolio decisions.     

The role of openness in the fuzzy front-end of service innovation

The early stages of innovation involve high levels of uncertainty, leading to it being labelled as the “fuzzy-front end” (FFE). Although openness has been identified as pivotal to innovation performance in the open innovation literature, little effort has been put into exploring its role in the FFE. Specifically, this study examines ‘openness competence’ within the FFE–i.e., the ability of a FFE team to explore, gather and assimilate operant resources from external sources by means of external searches and inter-organisational partnerships. The aim is to investigate the impact of openness competence on front-end uncertainty reduction and service innovation success. Data were obtained from a survey of 122 IT-based service innovation projects implemented by IT service provider firms in Thailand. The results suggest that openness competence positively influences both the degree of uncertainty being reduced during the FFE and the overall success of service innovations. These findings offer several implications for research on open innovation and the FFE as well as encouragement to managers to apply a more open approach to the FFE of their service innovation projects.     

Service quality of airports' food and beverage retailers. A fuzzy approach

Nowadays the profitability of airports is largely based on non-aeronautical or commercial activities, and particularly on retail and food and beverage services. Further, researchers concur that shopping, eating and drinking in airports have to be considered an important part of tourists' experience and activities that can significantly enhance or damage the tourist destination image. Despite this, there is still little research that analyses how service quality (SQ) is perceived by passengers consuming food and beverages (F&B) in airport areas. This study aims to deepen the scientific debate on this topic. Specifically, this study applies fuzzy numbers with a sample of 551 passengers flying from Olbia-Costa Smeralda Airport (Sardinia Region, Italy) with the aim of determining how they perceive the SQ delivered by F&B retailers and whether age plays a determinant role in segmentation. Findings reveal which F&B features outperform others; furthermore, they show that age is a moderating factor in consumer satisfaction, with older passengers being less satisfied than their counterparts. This study adds knowledge to the literature devoted to SQ, applying a fuzzy number approach to the under-investigated research area related to F&B consumption in airport areas. Further, it provides information useful to airport managers on the features of F&B services that are most important in shaping consumer satisfaction, based also on their age. Limitations of the study are also discussed and suggestions for future research are given.     

How can Taiwan create a niche in Asia's cruise tourism industry?

Cruise tourism is a significant growth trend in Europe and America. However, in recent years, it has gradually gained popularity among tourists in Asia, showing great potential. Strategically located in Asia, Taiwan is an ideal place to develop cruise tourism. This study explores how Taiwan could build a niche in Asia's cruise tourism industry. It applies the Fuzzy Delphi and Fuzzy IPA methods. According to study results, Taiwan should prioritize on the following aspects: establishing a 24-h tourist service center, providing a complete cruise logistics service, inviting foreign cruise operators to inspect special resources in Taiwan, cooperating with other Asian countries, setting up a special government unit, as well as planning and developing unique tourism resources.     

创新生态系统如何驱动企业微创新——一个组态视角的fsQCA分析

近年来,微创新是创新研究领域的热点,如何驱动企业微创新是相关研究亟需回答的问题。整合创新生态系统3个层面六大要素,运用模糊集定性比较分析（fsQCA）方法,以18个微创新案例为样本,探讨创新生态系统驱动企业微创新的复杂因果机制。结果发现：第一,单个创新生态系统要素并不构成企业高微创新的必要条件。第二,存在3条高微创新驱动路径,即机会识别主导下的用户驱动型、机会识别主导下的环境与用户参与驱动型,以及机会识别主导下的环境、组织学习与领先用户驱动型。此外,非高微创新驱动路径仅有一条,且与高微创新驱动路径存在非对称关系。第三,机会识别能力作为核心条件出现在高微创新的3个组态及非高微创新一个组态中,说明机会识别能力对企业微创新具有重要作用。     

什么样的数字创新生态系统能提高区域创新绩效——基于NCA与QCA的研究

什么样的数字创新生态系统有助于提高区域创新绩效是亟待解决的热点问题。采用必要条件分析（NCA）和模糊集定性比较分析（fsQCA）两种方法,对我国内地31个省（区、市）进行实证分析。研究发现：①数字企业、政府、高校及科研机构、数字创新基础设施、数字人才和金融服务是数字创新生态系统的关键构成,但单个要素并不是提高区域创新绩效的必要条件;②4种数字创新生态系统要素组态有助于提高区域创新绩效,构成的数字创新生态系统分别是政府引导的智力聚集型、企业开拓的环境支撑型、主体多元的综合发展型和企业主导的资本驱动型;③各地应因地制宜,选择合适的数字创新生态系统,培育区域创新新动能,助推“数字中国”新发展。     

数字赋能企业商业生态系统跃迁升级的机理及路径研究

数字技术应用融合叠加商业模式创新催生商业生态新业态,实现跃迁升级。本文结合扎根理论与模糊集定性比较分析(FsQCA)方法,阐释数字赋能企业商业生态系统跃迁升级的机理,探究多重组态路径。从生态视角揭示了数字资源通过与传统要素资源融合释放数据价值,并驱动形成价值循环体系、实现价值共创、塑造商业群落,最终实现企业商业生态系统跃迁升级。基于FsQCA的多组态分析发现,数字赋能企业商业生态系统跃迁升级历经两个阶段分别为价值共创和商业群落生成。其中,价值共创实现有两条组态路径,即产品创新与要素融合相组合,技术融合同低产品创新、低数据资产相组合,且产品创新构成了价值共创的核心条件。商业群落生成的组态路径表现出以下特征：价值共创和价值链接协同下分别和网络组织、数据赋能相组合,网络组织和数据赋能互为替代,即在一方缺失时,分别与价值共创或价值链接组合实现商业群落构建。本研究为企业商业生态系统的结构与功能持续优化,实现数字商业生态资源的充分共享及最优利用,提供了关键方法和思路。     

基于模糊层次分析法的合同能源管理项目风险综合评价

以合同能源管理项目为研究对象,结合我国社会经济发展现状,分析了我国合同能源管理项目实施过程中存在的政策与市场、融资以及运营与效益三方面风险,并运用模糊层次分析法对合同能源管理项目进行了风险评价。     

基于模糊综合评价法的市郊铁路客运站选址研究

本文针对其特点,应用层次分析法建立市郊铁路客运站站址比选的指标体系,确定各指标的权重,结合模糊综合评价原理建立相应的站址方案评价模型,并给出算例分析,为市郊铁路客运站站址方案的比选提供了一种更科学、更符合实际的方法。     

一种算法改进的模糊神经网络及其性能分析

将T-S模糊模型与前馈神经网络相融合构造了一种新型的模糊神经网络,该模型采用基于梯度下降法和算法相结合的混合学习方法,其中梯度下降法用来训练高斯型隶属度函数的非线性参数,而算法用来训练线性参数,即权值。从理论上,证明了该模型对非线性函数的万能逼近能力。仿真实验表明,该模糊神经网络用于非线性动态系统辨识的有效性。