Revisiting IS research practice in the era of big data

Through building and testing theory, the practice of research animates data for human sense-making about the world. The IS field began in an era when research data was scarce; in today's age of big data, it is now abundant. Yet, IS researchers often enact methodological assumptions developed in a time of data scarcity, and many remain uncertain how to systematically take advantage of new opportunities afforded by big data. How should we adapt our research norms, traditions, and practices to reflect newfound data abundance? How can we leverage the availability of big data to generate cumulative and generalizable knowledge claims that are robust to threats to validity? To date, IS academics have largely welcomed the arrival of big data as an overwhelmingly positive development. A common refrain in the discipline is: more data is great, IS researchers know all about data, and we are a well-positioned discipline to leverage big data in research and teaching. In our opinion, many benefits of big data will be realized only with a thoughtful understanding of the implications of big data availability and, increasingly, a deliberate shift in IS research practices. We advocate for a need to re-visit and extend traditional models that are commonly used to guide much of IS research. Based on our analysis, we propose a research approach that incorporates consideration of big data—and associated implications such as data abundance—into a classic approach to building and testing theory. We close our commentary by discussing the implications of this hybrid approach for the organization, execution, and evaluation of theory-informed research. Our recommendations on how to update one approach to IS research practice may have relevance to all theory-informed researchers who seek to leverage big data.     

Integrating quality into quantity: survey research in the era of mixed methods

As widely recognized during the golden age of survey research thanks to the work of the Columbia school, the use of mixed strategies allows survey research to overcome its limitations by incorporating the advantages of qualitative approaches rather than seeking alternative methods. The need to re-think survey research before embarking on this course impelled the author to undertake a critical analysis of one of the survey’s most important assumptions, proposing a shift from standardization of stimulus to standardization of meanings in order to anchor the requirement of answer comparability on a more solid basis. This proposal for rapprochement with qualitative research is followed by a more detailed section in which the author distinguishes four different types of mixed survey strategies, combining two criteria (time order and function of qualitative procedures). The most significant parts of the constructed typology are then brought together in a model called the multilevel integrated survey approach. This methodological model is concretely illustrated in an empirical study of homophobic prejudice among teenagers. The example shows how in research practice analytical mixed strategies can be creatively combined in the same survey research design, contributing to improvements in data quality and the relevance of research findings.     

大数据时代背景下浅议人才科研能力培养与企业应用

大数据时代呼唤创新性,懂得数据应用技术和研究创造的人才,会更受青睐。如今越来越多的企业在招聘人才时,更多地关注求职应聘者沟通相处能力,创新动手能力甚至管理能力的综合素质,以适应岗位要求和变化的社会环境。创新人才的培养,在高校教育中体现为对学生科研能力的教育要求。对本科生培养大数据意识,重视基本的学习信息采集和信息分析技术,更好的为企业提供运营管理和决策咨询服务。     

互联网时代对传统企业营销的影响及应对措施研究

文章分析了互联网时代企业营销的转变,以及互联网时代对企业营销的影响,并阐述了互联网时代企业营销转变的出路及应对措施。     

网上银行业务发展初探

文章就网上银行的特点,我国网上银行业务发展状况、存在问题及解决措施进行了初步探讨。     

Stability and integrity tests in data envelopment analysis

Studies that apply data envelopment analysis often neglect testing the stability of the efficient frontier to data perturbations, and, to a lesser extent, the ability of efficiency scores to correctly discriminate between units on performance (integrity). Our primary motivation is to demonstrate methods that can help reduce the number of managerial decisions based on results that may be unreliable. To this end, we illustrate multiple tests of stability and integrity in an environment of fully units-invariant efficiency measurement. This application of tests of stability and integrity using a slacks-based measure of efficiency is the first in a peer-reviewed journal.     

大数据时代下国内企业竞争情报研究分析

21世纪的人类社会是一个信息大爆炸的社会,各种各样的信息数据充斥在每一个角落,我们已经不可逆转地进入了大数据时代。文章基于大数据时代背景,论述了当前国内企业竞争情报研究状况,新的数据环境下企业竞争情报中所凸显的问题,以及对这些问题的分析与展望。     

互联网金融促进经济增长机制研究

本文从互联网金融促进经济增长机制的视角出发,在论证它是一类金融模式,归纳出它具有普惠金融、创新、知识技术密集型、产业集群化发展、支付快捷、交易成本低、信息透明和风险显性伴生等特点的基础上,引入马克思关于经济增长的理论,构建放松的古典—马克思经济增长模型,分析互联网金融通过提升资本保存率,增加资本积累,促进人力资本提升,在技术、产品和服务等领域的多重叠加创新,促进产业融合,降低经济发展成本等多种机制,能够促进社会经济增长.最后根据我国互联网金融发展现状提出几点建议.     

中国当代城市经济理论研究的沿革与发展

城市经济是国民经济的重要领域,对城市经济理论的研究,中国当代学者始终没有停下脚步,尤其是改革开放以来,开展了精彩而深刻的探索,取得了大量的成果。本文旨在梳理、揭示和反映中国当代城市经济理论研究的波澜壮阔的历程。     

浅谈大数据时代如何加强国有企业的财务管理

在数字信息技术的蓬勃发展下,大数据时代已经来临。文章分析了大数据时代给国有企业带来的新机遇和新挑战,在分析了国有企业财务管理亟需加强的关键点后,最后给出了相关建议。     

Problems in the estimation and interpretation of the reliability of survey data

In this paper I discuss several of the difficulties involved in estimating the reliability of survey measurement. Reliability is defined on the basis of classical true-score theory, as the correlational consistency of multiple measures of the same construct, net of true change. This concept is presented within the framework of a theoretical discussion of the sources of error in survey data and the design requirements for separating response variation into components representing such response consistency and measurement errors. Discussion focuses on the potential sources of random and nonrandom errors, including “invalidity” of measurement, the term frequently used to refer to components of method variance. Problems with the estimation of these components are enumerated and discussed with respect to both cross-sectional and panel designs. Empirical examples are given of the estimation of the quantities of interest, which are the basis of a discussion of the interpretational difficulties encountered in reliability estimation. Data are drawn from the ISR's Quality of Life surveys, the National Election Studies and the NORC's General Social Surveys. The general conclusion is that both cross-sectional and panel estimates of measurement reliability are desirable, but for the purposes of isolating the random component of error, panel designs are probably the most advantageous.     

Would you mind completing this survey: Assessing the state of survey research in supply chain management

In supply chain management, survey research is one of the primary methodologies used by researchers to generate empirical data. Critical to its effectiveness is an acceptable response rate. Recently, concerns have been raised regarding perceived falling response rates. Using data taken from 464 survey-based studies, as drawn from five representative journals that publish survey-based supply chain studies, this study assesses whether these concerns are valid. Furthermore, it assesses whether the various tactics recommended for improving response rates have been successful. The findings indicate that (1) responses rates have been falling (with a significant decrease beginning in 2001); (2) it is difficult to evaluate the effectiveness of the various techniques because of unevenness in reporting of techniques used; and, (3) response rates are significantly influenced by factors such as the number of questions, source of survey population, method of survey delivery, specific respondents targeted, and use of prequalification/pre-notification.     

金融市场羊群行为理论研究综述

近10年来,对金融市场上羊群行为的研究迅速成为金融经济学的热点之一。文章介绍了金融市场上羊群行为的概念,系统地回顾了羊群行为的理论研究成果,并展望了金融市场羊群行为理论研究的未来发展方向。     

Comparative research in industrial relations: helping the survey cross frontiers

There has been a relative dearth of comparative, cross-national research which has followed a survey-based approach. This partly reflects the difficulty that researchers encounter in collecting such information, either via primary collection or the secondary matching of existing survey material. This paper addresses these difficulties and suggests ways in which their impact can be minimized. It notes that such difficulties are much more severe in the case of secondary matching and are thereby likely to constrain the scope of this approach. They are not totally absent in primary collection and it is suggested that there are limits to what can be achieved during data collection to promote the development of like data-sets across countries. This indicates that great care must be taken in interpreting data so obtained. Despite such limits and cautions, it is nevertheless concluded that the survey approach can be an important adjunct to the process of understanding why the world of work varies across frontiers.     

On estimating the median from survey data using multiple auxiliary information

A new method to derive confidence intervals for medians in a finite population is presented. This method uses multi-auxiliary information through a multivariate regression type estimator of the population distribution function. A simulation study based on four real populations shows its behaviour versus other known methods.     

大数据在工业制造业的应用与研究

大数据时代,工业领域将会以想像不到的速度创新,呈现出新的技术、新的产品、新的服务和新的业态。各行各业的决策正在从业务驱动转变数据驱动。事实上,无论工业4.0还是工业互联网,其主要特征都是智能和互联,而主旨都在于通过充分利用信息通讯技术,把产品、机器、资源和人有机结合在一起,推动制造业向基于大数据分析与应用基础上的智能化转型。智能制造时代的到来,也意味着工业大数据时代的到来。工业大数据的应用,将成为未来制造业大创新的关键要素,也是目前全球工业转型必须面对的重要课题。     

高级编程语言中XML数据绑定的应用与研究

文章探讨了常用XML解析方法中数据绑定的优势和适用范围,并比较了C++、Java、VisualStudio.NET等高级编程语言中XML数据绑定的技术实现方式。