Addressing barriers to big data

Increasingly, big data is viewed as the most strategic resource of the 21st century, similar in importance to gold and oil. While sitting on these vast pools of data, many organizations are simply not ready to take advantage of this new strategic resource. Embracing big data requires addressing a number of barriers that fall into the domains of technology, people, and organization. A holistic, socio-technical approach is required to overcome these barriers. This article introduces the specific tactics we recommend for addressing big data barriers, which involve changes to technology infrastructure, a focus on privacy, promotion of big data and analytic skills development, and the creation of a clear organizational vision related to big data.     

Big data: Dimensions,evolution, impacts,and challenges

Big data represents a new technology paradigm for data that are generated at high velocity and high volume, and with high variety. Big data is envisioned as a game changer capable of revolutionizing the way businesses operate in many industries. This article introduces an integrated view of big data, traces the evolution of big data over the past 20 years, and discusses data analytics essential for processing various structured and unstructured data. This article illustrates the application of data analytics using merchant review data. The impacts of big data on key business performances are then evaluated. Finally, six technical and managerial challenges are discussed.     

The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources

Big data analytics have transformed research in many fields, including the business areas of marketing, accounting and finance, and supply chain management. Yet, the discussion surrounding big data analytics in human resource management has primarily focused on job candidate screenings. In this article, we consider how significant strategic human capital questions can be addressed with big data analytics, enabling HR to enhance overall firm performance. We also examine how new data sources that help assess workforce performance in real time can assist in the identification and development of the knowledge stars that contribute to firm performance disproportionately as well as help reinforce firm capabilities. But in order for big data analytics to be successful in the HR field, regulatory and ethical challenges must also be addressed; these include privacy concerns and, in Europe, the General Data Protection Regulation (GDPR). We conclude by discussing how big data analytics can facilitate strategic change within HR and the organization as a whole.     

The Role of Big Data and Predictive Analytics in Retailing

The paper examines the opportunities in and possibilities arising from big data in retailing, particularly along five major data dimensions—data pertaining to customers, products, time, (geo-spatial) location and channel. Much of the increase in data quality and application possibilities comes from a mix of new data sources, a smart application of statistical tools and domain knowledge combined with theoretical insights. The importance of theory in guiding any systematic search for answers to retailing questions, as well as for streamlining analysis remains undiminished, even as the role of big data and predictive analytics in retailing is set to rise in importance, aided by newer sources of data and large-scale correlational techniques. The Statistical issues discussed include a particular focus on the relevance and uses of Bayesian analysis techniques (data borrowing, updating, augmentation and hierarchical modeling), predictive analytics using big data and a field experiment, all in a retailing context. Finally, the ethical and privacy issues that may arise from the use of big data in retailing are also highlighted.     

Implementing big data strategies: A managerial perspective

Despite considerable recent advances in big data analytics, there is substantial evidence that many organizations have failed to incorporate them effectively in their own decision-making processes. Advancing the existing understandings, this article lays out the steps necessary to implement big data strategies successfully. To this end, we first explain how the big data analytics cycle can provide useful insights into the characteristics of the environments in which many organizations operate. Next, we review some common challenges faced by many organizations in their uses of big data analytics and offer specific recommendations for mitigating them. Among these recommendations, which are rooted in the findings of strategy implementation research, we emphasize managerial responsibilities in providing continued commitment and support, the effective communication and coordination of efforts, and the development of big data knowledge and expertise. Finally, in order to help managers obtain a fundamental knowledge of big data analytics, we provide an easy-to-understand explanation of important big data algorithms and illustrate their successful applications through a number of real-life examples.     

The perils of working with big data,and a SMALL checklist you can use to recognize them

The use of big data to help explain fluctuations in the broader economy and key business performance indicators is now so commonplace that in some instances it has even begun to rival more traditional measures. Big data sources can very often provide advantages when compared with these more traditional data sources, but with these advantages also come potential pitfalls. We lay out a checklist called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL checklist should help users of big data draw justifiable conclusions and avoid making mistakes in matters of interpretation. To demonstrate, we provide several case studies that demonstrate the subtle nuances of several of these new big data sets and show how the problems they face often closely relate to age-old concerns that more traditional data sources are also forced to tackle.     

Business curriculum redesign: Integrating data analytics

Data analytics is an integral part of planning and decision making in business. Priorities have shifted to hiring skilled employees to support a company’s analytics requirements. The authors discuss the background of big data and data analytics, demand for trained professionals, and information on the development of a data analytics curriculum. Curriculum design models are explored and emphasis placed on university curriculum redesign. This is a perspective piece that also addresses interdisciplinary collaboration, accreditation, and related challenges.     

The law and ethics of big data analytics: A new role for international human rights in the search for global standards

The Economist recently declared that digital information has overtaken oil as the world’s most valuable commodity. Big data technology is inherently global and borderless, yet little international consensus exists over what standards should govern its use. One source of global standards benefitting from considerable international consensus might be used to fill the gap: international human rights law. This article considers the extent to which international human rights law operates as a legal or ethical constraint on global commercial use of big data technologies. By providing clear baseline standards that apply worldwide, human rights can help shape cultural norms—implemented as ethical practices and global policies and procedures—about what businesses should do with their information technologies. In this way, human rights could play a broad and important role in shaping business thinking about the proper handling of this increasingly valuable commodity in the modern global society.     

The Impact of Ethical Ideologies,Moral Intensity,and Social Context on Sales-Based Ethical Reasoning

Previous research indicates that ethical ideologies, issue-contingencies, and social context can impact ethical reasoning in different business situations. However, the manner in which these constructs work together to shape different steps of the ethical decision-making process is not always clear. The purpose of this study was to address these issues by exploring the influence of idealism and relativism, perceived moral intensity in a decision-making situation, and social context on the recognition of an ethical issue and ethical intention. Utilizing a sales-based scenario and multiple ethics measures included on a self-report questionnaire, data were collected from a regional sample of business students, most of whom had modest work experience. The results indicated that perceived moral intensity was associated with increased ethical issue recognition and ethical intention. Idealism was also associated with increased ethical issue recognition, and relativism was associated with decreased ethical intention. Social consensus was positively related to ethical issue recognition and intention, while competitive context was inversely related to ethical intention. Finally, ethical issue recognition was associated with increased ethical intention. Idealism, moral intensity, social consensus, and work experience worked together as predictors of ethical issue recognition, whereas recognition of an ethical issue, relativism, moral intensity, social consensus, and competitive context worked together to predict ethical intention.     

Big data? Big deal: Searching for big data’s performance effects in HR

Big data continues to gather increasing interest in the business press as well as within the management literature. While this interest has spilled over into the realm of human resources (HR) management, solid evidence of its positive performance impacts is lacking. I explore three possibilities for this lack of evidence: (1) HR possesses big data but largely lacks the ability to use it; (2) HR does not actually possess big data; and (3) big data is generating value for HR and positively affects organizational performance, but the winners in the race to utilize big data in HR are not publicizing their successes. Following this, I discuss current forms of big data implementation, highlighting an evolutionary progression of implementations in various settings and emphasizing the importance of balancing deductive with inductive analytical approaches. Finally, I discuss conditions under which big data may hold greater value for the HR function, and I suggest ways managers and organizations can make the most of big data.     

Big data dreams: A framework for corporate strategy

The phenomenon of big data—large, diverse, complex, and/or longitudinal data sets—is having a stark influence on organizational strategy making. An increase in levels of data and technological capabilities is redefining innovation, competition, and productivity. This article contributes to both practical strategic application and academic research in the strategic management domain by presenting a framework that identifies how big data improves functional capabilities within organizations, shapes entirely new industries, and is a key component of innovative and disruptive strategies used by learning organizations to diversify and break down barriers of traditionally defined industries. This framework provides an appropriate basis for internal corporate strategy discussions that surround big data investments by explaining how firms create value through various approaches. In addition, we offer guidance for how firms might derive their own big data approach through the merits of aligning data strategy aspirations with data strategy authenticity.     

Marketing and Internet Professionals' Fiduciary Responsibility: A Perspective on Spyware

ABSTRACT

While Internet usage has become a widely accepted marketing vehicle, ethical issues continue to develop without clear guidance. Today controversies abound regarding “passive devices” technologies for collecting information about Internet users. Passive data collection techniques include such software devices as adware, cookies, spyware, and web bugs. This paper reviews these software devices and presents a “cultural lag” perspective to explain the lack of clear ethical guidelines for their use. Fiduciary considerations are proposed as a basis for ethical guidelines, codes of ethics of major computer programming, information systems, and marketing professional associations are reviewed, and recommendations are offered to facilitate the development and acceptance of appropriate guidelines.     

Big data

Big data is defined and distinguished from a mere moment in the “ancient quest to measure.” Specific discontinuities in the practice of information science are identified which, the paper argues, have large consequences for the social order. The infrastructure that runs on big data is described as diffusing with unprecedented speed but as being difficult to analyze and critique, and therefore the designers of society’s big data infrastructure, whether human or machines, play an unacknowledged legislative function of great consequence.     

The complexity of surveying web participation

Marketing managers increasingly need to understand how consumers use and interact with digital media, such as the web, social networks, mobile phones, digital readers, search engines and so forth. The focus of this paper is web participation and the complexities involved in measuring usage and interaction with the web, particularly when relying on data from self-report surveys. Few studies have specifically examined how web participation can be surveyed—this paper addresses the gap. First, web participation is defined by drawing on studies of web usage in information systems, consumer and communication research, and audience use metrics in media research. Second, web participation is discussed as a complex multi-dimensional construct, something that is not fully acknowledged in existing web use research. Third, major influences on self-reported web participation are considered, in particular the impact of a consumer's web design experience and the person's perceptions of web usability on how they self-report web participation. These themes are investigated using a large web-based survey. Findings show that a consumer's perception of web usability has a significant impact on the self-reporting of web participation, but this depends on how web participation is measured and whether the individual has website design experience. The complexity of surveying web participation is apparent, as is the importance of understanding the web's usage-context.     

Suggested Management Responses to Ethical Issues Raised by Technological Change

The development of technology raises an array of ethical issues related to work. Many of these ethical issues are old issues surfacing under new guises. Technology has not changed the issues, but technology makes the issues' analysis and application more complex. This paper identifies several new ethical issues raised by technological change: computer crime, an over-reliance on computer controlled systems, bio-technical developments, degradation of quality-of-life at work and new categories of work-related injuries. These issues are discussed in the context of management responsibilities and responses. The paper offers a five-step process for the effective management of these ethical issues: Be aware of the issues, develop an ethical framework, be consistent, communicate clearly, stay alert for future developments.     

大数据、人工智能与厂商竞争路径

经济学对市场竞争路径的学理性分析,主要集中在价格确定、产量确定、规模经济、产业组织等方面,而对科技进步引发市场竞争路径的变化并没有足够的关注。其实,市场竞争路径变化的底蕴是科技进步,只是经济学家在分析市场竞争路径时偏好于将科技因素作为外生变量处理。大数据和人工智能等的发展可谓是一场史无前例的科技革命,它对人类经济活动产生广泛而深刻的影响主要表现为：大数据及其运用怎样影响厂商投资经营,大数据与机器学习等人工智能手段相融合会在哪些方面改变厂商竞争路径,厂商如何提高数据智能化和实现网络协同化,在什么样的条件下会出现行业垄断,等等。文章的基本分析观点是：厂商竞争路径变化是贯穿于大数据、互联网和人工智能等相互融合过程的一种现象,这种现象对应于新科技进步和运用的不同层级;微观经济分析需要将新科技因素作为内生变量,通过分析大数据、机器学习与厂商竞争路径之间的关联,揭示厂商竞争路径变化机理以及由此引致的产业组织等问题。     

An Analysis of U.S. Disinvestment from South Africa: Unity, Rights, and Justice

This study examines the issues associated with the disinvestment of U.S. interests from South Africa that took place in the mid-80s from the perspective of three dominant moral theories: utility, rights, and justice. By examining the issues in light of these three theories, the paper attempts to establish a decision framework from which managers and investors can evaluate similar decisions they are facing around the world today. Similarly, the reading may prove useful to educators who incorporate discussions of ethical decision making into the classroom.Training in business ethics too often takes a strictly utilitarian perspective, or worse, a relativistic one. This study attempts to illustrate how utilitarian theory and related rights and justice issues can he interwoven into the heuristics associated with the contemporary concepts of corporate social responsibility.     

Enterprise Social Networking: Opportunities,Adoption, and Risk Mitigation

Social networks on the Internet are becoming extremely popular and have begun to change the way we live and work. Many enterprises are assessing the potential of exploiting the commercial opportunities of this technology. Although social networking commercial activities may be the next big productivity booster for firms, some consider such activities to be time wasters and security traps. Therefore, it is useful to develop a framework to consolidate the issues in adopting this technology. This article reviews the opportunities provided by enterprise social networking and proposes using the fit-viability model to evaluate concerns related to the successful implementation of enterprise social networking. We also examine the major potential risks and the mechanisms for their management.     

Interoperability: Our exciting and terrifying Web3 future

This article introduces the next major generational evolution of the web: Web3. We review the fundamental evolution of the internet and the web over the past 3 decades, including a brief presentation of the publications in Business Horizons that are important in a discussion of the emergence of Web3. We then discuss what these recent developments mean to organizations, consumers, and the public. Though the degree to which Web3 will be widely adopted is uncertain, these technologies are already creating both exhilarating and terrifying implications for e-commerce, digital media, online social networking, online marketplaces, search engines, supply chain management, and finance, among others. We propose the consideration and management of technical, organizational, and regulatory interoperability for Web3 to deliver on its promises of value and that failure to consider these interoperability components may destroy economic value, consumer confidence, or social issues online. We also call on our fellow researchers to focus on these interoperability issues and how they might impact the positive and negative sides of Web3 technologies to help us understand and shape our Web3 future.