A survey towards an integration of big data analytics to big insights for value-creation

Big Data Analytics (BDA) is increasingly becoming a trending practice that generates an enormous amount of data and provides a new opportunity that is helpful in relevant decision-making. The developments in Big Data Analytics provide a new paradigm and solutions for big data sources, storage, and advanced analytics. The BDA provide a nuanced view of big data development, and insights on how it can truly create value for firm and customer. This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies. It provides an overview of the architecture of BDA including six components, namely: (i) data generation, (ii) data acquisition, (iii) data storage, (iv) advanced data analytics, (v) data visualization, and (vi) decision-making for value-creation. In this paper, seven V's characteristics of BDA namely Volume, Velocity, Variety, Valence, Veracity, Variability, and Value are explored. The various big data analytics tools, techniques and technologies have been described. Furthermore, it presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city. This paper also highlights the previous research, challenges, current status, and future directions of big data analytics for various application platforms. This overview highlights three issues, namely (i) concepts, characteristics and processing paradigms of Big Data Analytics; (ii) the state-of-the-art framework for decision-making in BDA for companies to insight value-creation; and (iii) the current challenges of Big Data Analytics as well as possible future directions.     

The influence of informal social media practices on knowledge sharing and work processes within organizations

Contemporary information technologies such as social media have invigorated the way knowledge is shared within organizations to the extent that we have to rethink and reassess our understanding of the role and influence of technology in organizational processes and knowledge sharing. This paper uses the strategy as practice lens guided by the interpretivist philosophy to understand the influence of informal social media practices on knowledge sharing and work processes within an organization. The paper uses empirical evidence from the case study of a telecom organization in Tanzania to gain theoretical insight into informal social media practices and knowledge sharing. This research contributes to the Information Systems (IS) literature by asserting that organizational processes are achieved by mundane knowledge sharing mediated by informal social media use within the organization. Also, the study contributes to IS literature by highlighting how emerging informal practices are essential to daily processes within organizations.     

Building a compassionate workplace using information technology: Considerations for information systems research

This opinion paper presents the need for IS research on compassion in the organizational workplace. Given the current challenges caused by COVID-19, we argue that organizations need to be resilient to counter the adverse effects of this pandemic. Developing a compassionate organizational workplace is an effective way to build resilient organizations. The paper draws attention to the fact that a focus on compassion can be a valuable scope of inquiry within IS research. It proposes an integrative framework mapping the scope of compassion in IS research and develops a research agenda that can aid future inquiry into this phenomenon.     

Process reference frameworks as institutional arrangements for digital service innovation

Information systems (IS) service organizations are increasingly more concerned with their ability to co-create digital services with customers in service ecosystems. Practitioners and researchers, however, lack understanding of which organization mechanisms effectively contribute to IS organizations’ innovation practices. Grounded in service-dominant logic, we hypothesized that process reference frameworks (PRFs), such as the IT Infrastructure Library (ITIL), act as institutional arrangements through their norms, rules, and practices, enhancing IS organizations’ ability to innovate digital services. Data collected from 159 IS organizations confirmed our hypotheses, showing that effects on digital service innovation are mediated by an organization’s digital service climate and co-creation practices. This study makes four major contributions. First, our results contribute to the literature on service-dominant logic and the role of institutional arrangements in facilitating service innovation in service ecosystems. Second, our study offers a novel understanding of PRFs’ role in value co-creation and digital service innovation. Third, by introducing the digital service climate from existing theoretical frameworks that might assist in conceptualizing the role of culture and shared meaning, our study contributes to further theorizing on the social factors that influence service ecosystem practices. Finally, our findings can motivate IT managers to consider using PRFs to develop capabilities for creating business value together with customers.     

影响信息系统成功的个人行为模式研究探讨

信息系统的建设随着信息科技的发展而如火如荼,在技术层面上取得了长足进步,但因个人层面因素一般不易随技术发展而有较大的本质改变,往往就成了影响信息系统能否成功的主要因素.就国内外影响信息系统成功的个人层面的因素和行为模式进行研究,包括TAM、TPB等的分析,以期为我国信息系统的成功导入提供借鉴.     

A Big Data system supporting Bosch Braga Industry 4.0 strategy

People, devices, infrastructures and sensors can constantly communicate exchanging data and generating new data that trace many of these exchanges. This leads to vast volumes of data collected at ever increasing velocities and of different variety, a phenomenon currently known as Big Data. In particular, recent developments in Information and Communications Technologies are pushing the fourth industrial revolution, Industry 4.0, being data generated by several sources like machine controllers, sensors, manufacturing systems, among others. Joining volume, variety and velocity of data, with Industry 4.0, makes the opportunity to enhance sustainable innovation in the Factories of the Future. In this, the collection, integration, storage, processing and analysis of data is a key challenge, being Big Data systems needed to link all the entities and data needs of the factory. Thereby, this paper addresses this key challenge, proposing and implementing a Big Data Analytics architecture, using a multinational organisation (Bosch Car Multimedia – Braga) as a case study. In this work, all the data lifecycle, from collection to analysis, is handled, taking into consideration the different data processing speeds that can exist in the real environment of a factory (batch or stream).     

Strategies for meeting user demands: An international perspective

The role of the Data Processing or Information Department is to bridge the gap between the available information technology and the use and users of that technology in the organization at large. Changes in available technology and changes in the nature or scale of information use engender changes in the way the Information Department carries out its mediating role. The growth in the volume of end-user requests for systems, and the character of the systems requested, have made traditional DP methods inadequate. This has led to changes in the organization of work in these departments. This paper presents international survey data on a number of different strategies that have been used to enable Information Departments better to meet enduser demands. It considers factors which lead to the adoption of different strategies in different circumstances. Data from USA, Japan, UK and Scandinavia are used to examine some of the social and cultural factors which can influence the organization of the Information Department.     

Theory building with big data-driven research – Moving away from the “What” towards the “Why”

Data availability and access to various platforms, is changing the nature of Information Systems (IS) studies. Such studies often use large datasets, which may incorporate structured and unstructured data, from various platforms. The questions that such papers address, in turn, may attempt to use methods from computational science like sentiment mining, text mining, network science and image analytics to derive insights. However, there is often a weak theoretical contribution in many of these studies. We point out the need for such studies to contribute back to the IS discipline, whereby findings can explain more about the phenomenon surrounding the interaction of people with technology artefacts and the ecosystem within which these contextual usage is situated. Our opinion paper attempts to address this gap and provide insights on the methodological adaptations required in “big data studies” to be converted into “IS research” and contribute to theory building in information systems.     

Artificial intelligence for decision making in the era of Big Data – evolution,challenges and research agenda

Artificial intelligence (AI) has been in existence for over six decades and has experienced AI winters and springs. The rise of super computing power and Big Data technologies appear to have empowered AI in recent years. The new generation of AI is rapidly expanding and has again become an attractive topic for research. This paper aims to identify the challenges associated with the use and impact of revitalised AI based systems for decision making and offer a set of research propositions for information systems (IS) researchers. The paper first provides a view of the history of AI through the relevant papers published in the International Journal of Information Management (IJIM). It then discusses AI for decision making in general and the specific issues regarding the interaction and integration of AI to support or replace human decision makers in particular. To advance research on the use of AI for decision making in the era of Big Data, the paper offers twelve research propositions for IS researchers in terms of conceptual and theoretical development, AI technology-human interaction, and AI implementation.     

Patterns of co-alignment in information-intensive organizations: business performance through integration strategies

Information technology (IT) has transformed business practices in the last several decades: operations, product strategies, distribution, and customer service have become increasingly dependent on IT. Moreover, IT has changed its orientation from that of pure operational utility in the 1960s and 1970s to that of a competitive weapon in the 1990s and today. These phenomena have affected the way modern organizations are managed, as well as the way IT affects the strategic activities of an organization's value-chain.In particular, aligning an organization's business and IT strategies in order to deliver higher business performance presupposes a strategic business opportunity to which information systems technology is integral. In other words, Strategic Alignment between business and IT can have a positive business impact only if we see an organization's IT components as parts of a well-integrated organizational system. If business strategy is viewed separately from IT strategy or IT strategy is viewed only as a “support” tool, then there is little likelihood that the above positive impact of strategic alignment can take place.This research suggests, develops and tests a strategic co-alignment model by examining three types of integration that impact the planning process and the overall performance of information-intensive organizations: technological integration (TI), functional integration and strategic integration (SI).The results of this research yield some useful set of guidelines for theory building for IS, as well as for the business practice aspect of IS: most interesting is the role of consistency (co-alignment) between an organization's business and strategic information systems plans to improve overall firm performance. Other recommendations include having a high degree of involvement of IS executives in corporate planning, the use of outsourcing services to promote organizational systems integration, and the importance of internal coordination mechanisms to facilitate both systems consistency and lower transaction costs. Finally, this study has employed cluster analysis and discriminant analysis to interpret the research findings.     

Big Data Analytics in Building the Competitive Intelligence of Organizations

Over recent years, organizations have started to capitalize on the significant use of Big Data and emerging technologies to analyze, and gain valuable insights linked to, decision-making processes. The process of Competitive Intelligence (CI) includes monitoring competitors with a view to delivering both actionable and meaningful intelligence to organizations. In this regard, the capacity to leverage and unleash the potential of big data tools and techniques is one of various significant components of successfully steering CI and ultimately infusing such valuable knowledge into CI strategies. In this paper, the authors aim to examine Big Data applications in CI processes within organizations by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations. Overall, research findings have indicated a preference for a rather centralized informal process as opposed to a clear formal structure for CI; the use of basic tools for queries, as opposed to reliance on dedicated methods such as advanced machine learning; and the existence of multiple challenges that companies currently face regarding the use of big data analytics in building organizational CI.     

“Context” in healthcare information technology resistance: A systematic review of extant literature and agenda for future research

Resistance to Healthcare Information Technologies (HIT) continues to be a major challenge that hampers the realization of benefits. Attending to the noted significance of “context” in IT resistance, we carried out this review to understand how the “context” of healthcare in the extant HIT resistance literature has been studied. Based on a review of HIT resistance across 19 IS journals and 5 major IS conferences we organize and summarize the literature around the interaction of people, practice, and technology and provide several significant possibilities for future research.     

信息系统成长理论演进中的关键因素转移规律研究

本文梳理了自计算机化的信息系统产生以来,学者们对其发展规律和关键成长因素的研究。通过比较分析,指出影响IS成长的关键因素随着时间的发展,发生了遵从一定规律的转移,即从硬因子转向软因子。通过对转移规律的总结和内在原因分析,笔者指出了现代企业建设信息系统的重点和未来研究方向。     

Understanding the impact of digital service failure on users: Integrating Tan’s failure and DeLone and McLean’s success model

Although information systems (IS) success has been given much attention in IS literature, failure has received lesser attention. This study empirically validates a model of digital service failure for consumers by integrating three dimensions from Tan’s failure model and one dimension from DeLone and Mclean’s Information Success model. The factors have been mapped to Expectation Disconfirmation Theory (EDT). Experiential survey approach has been used to collect primary data from information systems users who have experienced digital service failure. Structural equation modeling (SEM) has been used for model testing and validation to measure the impact of information, system, functional and service failure of digital service on end users. The findings suggests that information, functional, system and service failure has an impact on the consumers through the outcome, process, cost and user satisfaction of digital services.     

XML在医院信息系统中的应用

XML以其合理的数据组织结构和可扩展的特性，成为各种复杂数据，特别是半结构化数据表示和处理的良好工具。本文介绍了XML及XML在医院信息系统（HIS）中的应用，尤其在电子病历方面的应用，包括XML数据在电子病历中的数据存储与系统结构。     

EVALUATING THE PRACTICES OF FLEXIBILITY MATURITY FOR THE SOFTWARE PRODUCT AND SERVICE ORGANIZATIONS

The competitive advantage offered by flexibility has drawn considerable attention from the academic and practitioner community. The existing literature primarily focuses on means to achieve flexibility through information system (IS) exploitation. There is a noticeable absence of a comprehensive flexibility evaluation and implementation framework for organizations, engaged in the delivery of software products and services. This paper proposes twenty-three practices graded in six maturity levels to fill this gap. These practices will improve the understanding, evaluation, and implementation of flexibility in the organizational setting.     

基于网络论坛的信息系统双向知识转移的影响因素研究

摘要：本文探讨在信息系统外包或购置商品软件开发方式下,IS外部提供方与IS需求方的个体之间,信息系统双向知识转移的影响因素。首先在知识转移、信息系统理论的文献基础上,形成一个理论模型,假定信息系统双向知识转移受知识相关因素（共识）、交流相关因素（双向信任、双方的交流能力）的影响。然后采用无干扰实证研究方法,基于讨论信息系统知识的网络论坛,模拟实际情况,收集数据进行回归分析,论证了12项假设中的10项,证实了这两组影响因素与双向知识转移的关系。     

信息系统习惯对持续使用影响的研究述评与过程性框架

明晰信息系统习惯的概念和测量,借鉴心理学有关习惯的理论研究成果,评述持续使用研究中有关信息系统习惯的前因与后果的实证研究,发展提出信息系统习惯性框架——习惯的发展过程可为形成、保持和破裂阶段,并深入分析了信息系统习惯在三阶段不同的作用机制。最后,从研究内容和实证检验两方面为未来研究提出建议。     

Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronics industry

The advent of new information technology has radically changed the end-user computing environment over the past decade. To enhance their management decision-making capability, many organizations have made significant investments in business intelligence (BI) systems. The realization of business benefits from BI investments depends on supporting effective use of BI systems and satisfying their end user requirements. Even though a lot of attention has been paid to the decision-making benefits of BI systems in practice, there is still a limited amount of empirical research that explores the nature of end-user satisfaction with BI systems. End-user satisfaction and system usage have been recognized by many researchers as critical determinants of the success of information systems (IS). As an increasing number of companies have adopted BI systems, there is a need to understand their impact on an individual end-user's performance. In recent years, researchers have considered assessing individual performance effects from IS use as a key area of concern. Therefore, this study aims to empirically test a framework identifying the relationships between end-user computing satisfaction (EUCS), system usage, and individual performance. Data gathered from 330 end users of BI systems in the Taiwanese electronics industry were used to test the relationships proposed in the framework using the structural equation modeling approach. The results provide strong support for our model. Our results indicate that higher levels of EUCS can lead to increased BI system usage and improved individual performance, and that higher levels of BI system usage will lead to higher levels of individual performance. In addition, this study's findings, consistent with DeLone and McLean's IS success model, confirm that there exists a significant positive relationship between EUCS and system usage. Theoretical and practical implications of the findings are discussed.     

组织在惰性氛围下如何进行商业模式创新？

企业在发展的过程中可能会形成惰性,使其商业模式无法快速响应市场需求的变化,阻碍了可持续发展,因此,在惰性的氛围下如何推动商业模式创新,是企业亟待解决的问题。但当前管理学中惰性的相关研究较少关注商业模式创新领域,从而导致对从惰性到商业模式创新的过程缺乏深入的探究。基于此,论文以在新零售背景下进行商业模式创新的传统零售企业为研究对象,通过扎根理论方法,构建出组织在惰性氛围下的商业模式创新过程模型,以探究组织从惰性到商业模式创新的过程机理,研究发现：（1）环境压力促使组织对当前的惰性特征进行反思,从而增强商业模式创新的动机;（2）组织需要综合运用主动遗忘、组织学习与组织借用三种方式来减弱对原有商业模式的依赖,并进行商业模式的探索、借鉴与尝试,而这一知识建构过程受到网络嵌入的影响;（3）在知识建构的基础上增强组织即兴能力,更有利于降低组织即兴的不确定性和风险性,促进商业模式创新。在此基础上,论文对研究结果进行了讨论,并提出相关建议。