Healthcare and hospitality: intangible dynamics for evaluating industry sectors

In order to assess potentially profitable exchanges across the healthcare and hospitality industries, this paper reviews intangibles theory, ranging from big data through knowledge assets (explicit and tacit) to intelligence, establishing the potential value from each and best practices for managing. Metrics are offered for the assessment of firms and industries according to these intangibles. Based on the metrics, intangible practices can be identified in all the industry sectors across healthcare as well as from hospitality sectors. Similarities are identified between hospitality and specific healthcare sectors (retail pharmacies have most in common with hospitality firms, both possessing strong data and explicit knowledge capabilities). Implications for strategy, competition, and intangibles management systems can also be drawn (chiefly process and customer relationship data and knowledge leading to operational and marketing excellence).     

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.     

How talent capability can shape service analytics capability in the big data environment?

We know very little about how big data-driven service analytics capabilities (SAC) are built in data-driven service organizations and the potential role of talent capability in facilitating overall SAC and the impact of both on firm performance (FPER). Drawing on the dynamic capabilities (DC) approach, this study investigates the link between SAC and FPER examining the mediating role of talent capability and the moderating influence of a firm’s strategic alignment. On the basis of two Delphi studies and survey data from 267 service analysts in the US and France, the findings show that even though SAC are built on technology, talent and information capabilities, their overall impact on firm performance is mediated by the level of talent capability of service analytics managers. The findings also confirm the critical moderating impact of strategic alignment between dynamic talent capability and firm performance in the big data environment.     

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.     

企业国际化研究新视角 ——战略控制力

本文针对现有企业国际化理论缺乏战略因素综合考虑的研究现状,从战略控制力的视角对企业国际化问题进行研究,剖析了企业国际化战略控制力的内涵与特征,并提出了国际化战略控制力五要素,指出国际化战略控制力是维持企业国际化持续发展和优胜地位的根源,同时对中国大企业国际化战略控制力的构建问题进行了有益探讨。     

Siri,Siri, in my hand: Who’s the fairest in the land? On the interpretations,illustrations, and implications of artificial intelligence

Artificial intelligence (AI)—defined as a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation—is a topic in nearly every boardroom and at many dinner tables. Yet, despite this prominence, AI is still a surprisingly fuzzy concept and a lot of questions surrounding it are still open. In this article, we analyze how AI is different from related concepts, such as the Internet of Things and big data, and suggest that AI is not one monolithic term but instead needs to be seen in a more nuanced way. This can either be achieved by looking at AI through the lens of evolutionary stages (artificial narrow intelligence, artificial general intelligence, and artificial super intelligence) or by focusing on different types of AI systems (analytical AI, human-inspired AI, and humanized AI). Based on this classification, we show the potential and risk of AI using a series of case studies regarding universities, corporations, and governments. Finally, we present a framework that helps organizations think about the internal and external implications of AI, which we label the Three C Model of Confidence, Change, and Control.     

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.     

Big web data: Challenges related to data,technology, legality,and ethics

The digital data available online is currently measured in zettabytes. These vast repositories of big web data are increasingly viewed as a strategic resource comparable in value to land, gold, and oil. This big web data can be extracted and analyzed by organizations to gain a better understanding of their internal and external environment and improve organizational performance. Because of these opportunities, automated retrieval and organization of web data (i.e., web scraping) for research projects is becoming a common practice. This article outlines the data-related, technical, legal, and ethical issues related to web scraping. Awareness of these issues can help researchers save time and resources and, most importantly, mitigate the potential risk of ethical controversies or lawsuits related to the retrieval and use of big web data.     

Hierarchical Dynamic Capabilities and Strategic Entrepreneurship in Changing Industrial Environments

The research fields of dynamic capabilities and strategic entrepreneurship have developed concurrently but separately. This study aims to bridge the gap in research on the underlying linkage between the two independent areas, both of which are critical for firms to sustain competitiveness in changing industrial environments. Drawing upon insights from the integrated perspective of hierarchical dynamic capabilities, strategic entrepreneurship, and environmental dynamics, an explicit theoretical framework is put forward to achieve a better understanding of the ways through which hierarchical dynamic capabilities promote strategic entrepreneurship. Moreover, through the proposed theoretical lens, this study further explores the detailed mechanisms of how first-order and second-order dynamic capabilities improve strategic entrepreneurship with regard to uncertainty of market conditions.     

How Knowledge Management Capabilities Help Leverage Knowledge Resources and Strategic Orientation for New Product Advantages in B-to-B High-Technology Firms

ABSTRACT

Purpose: Current understanding of how new product development (NPD) teams use knowledge management capabilities to acquire, disseminate, and apply knowledge resources to achieve competitive advantages is limited by a lack of compelling theory supported by empirical evidence. This study provides a theoretical framework and empirical validation for how an NPD team manages knowledge resources and strategic orientation to enhance its knowledge management capabilities, which, in turn, lead to business-to-busienss (B-to-B) new product advantages.

Methodology/approach: A total of 100 sets of data was collected from B-to-B firms in U.S. high-tech industries. In order to validate the proposed hypotheses, we estimated the main effects using path analysis in AMOS, and tested for interaction effects using interaction term regressions.

Findings: Our findings show that the two dimensions of NPD knowledge management capabilities—acquisition and application—are important but differential drivers of product quality superiority and product differentiation. In testing whether NPD management capabilities matter for two product advantage constructs, we confirmed that product quality superiority can be enhanced by both NPD knowledge acquisition and application capabilities, whereas product differentiation can be increased strongly by NPD knowledge acquisition capabilities.

Research implications: Our research confirms the importance of strategic orientation as a driver of NPD knowledge management capabilities, which enhances understanding of how strategic factors operate under a resource-based view. Our results further provide direct empirical support for the knowledge-based view of firms, in that an NPD team’s abilities to manage and deploy knowledge-based resources by acquiring and applying NPD knowledge lead to competitive advantages, for outcomes of quality superiority and differentiation.

Practical implications: Our findings have relevance for managers in three ways. First, NPD knowledge acquisition and application capabilities have differential impacts on product quality superiority and differentiation. Second, in exploring NPD resource factors as antecedents, managers should manage levels of NPD market intelligence, resource tacitness, and NPD resource deployment differentially to directly improve NPD teams’ acquisition and application capabilities. Third, managers should not underestimate the importance of market and technological orientations in enhancing NPD knowledge management capabilities. Market orientation drives both NPD knowledge acquisition and application capabilities; technological orientation drives NPD knowledge application capabilities. Originality/value/contribution of the paper: An NPD team’s knowledge management capabilities generally, but differentially, mediate the relationships of knowledge resources and strategic orientation factors with new product competitive advantage. However, simply enhancing NPD knowledge management capabilities is not a panacea for developing product competitive advantage in B-to-B settings, because of their differential effects.     

Strategy shift: Integrating strategy and the firm’s capability to innovate

Innovation is a key source of organizational growth and profitability. Many organizations at the front end of innovation struggle to engender an innovation approach that is effective and lasting. This article presents a framework that defines the interdependency of innovation and strategy, and then outlines the role of top management to continuously renew the positioning of the firm. Based on a synthesis of prior research—including the Dynamic Capabilities View, Innovation Orientation, and Disruptive Innovation Theory—and our own experience working with organizations, we present an operational strategy shift framework, which allows practitioners to increase, refine, and transform their firm’s capability to innovate (CTI) toward achieving their strategic objectives. This framework provides guidance that leaders can use to integrate innovation into their strategic process.     

基于大数据推进海关智慧稽查建设的框架设想

近年来,随着行为记录数据化的普及和数据价值挖掘能力的提升,大数据在工业、农业、经济、政府管理等各个领域得到充分应用并蓬勃发展。随着全国通关一体化改革和海关稽查改革的深入推进,稽查部门如何在"通得快"的前提下保障后续监管"管得严",如何以有限的人力资源承担不断增长的后续监管任务,如何以创新的理念和工作方法应对日新月异的贸易实际和监管要求,是摆在稽查人面前的重大课题和长期任务。智慧海关建设成为海关全面深化改革的重要内容。本文从当前稽查工作中存在的问题及大数据应用的现状切入,对推进智慧稽查进行必要性分析,并提出智慧稽查建设的框架设想及具体举措,其目的是通过智慧化管理,推进稽查执法的规范、便捷、高效。     

Contrasting Strategic Response to Economic Recession in Start‐Up versus Established Software Firms*

Economic recessions represent a period of greatly reduced environmental munificence that threatens the survival of all firms. This is especially the case for smaller, start‐up firms, which have been shown to fail at a much higher rate compared with their larger, more established peers. This study surveyed 137 software executives regarding their strategic response to the most recent economic downturn (2001–2003). I draw upon Hofer's framework for turnaround strategies to develop hypotheses to explore how smaller, start‐up firms adjust their strategies in response to economic recession. The results suggest that start‐up organizations are much more inclined to pursue revenue‐generating strategies as a means to weathering recession rather than cost reductions, which tended to be the preferred strategy of larger firms.     

Knowledge, values and internationalisation—introduction to the special edition

Internationalisation is increasingly being seen as an organisational learning process. However, entrepreneurial enterprises tend to be smaller, more innovative and more agile than their larger counterparts. When they internationalise, entrepreneurial firms often expand at a rapid rate. The cultures of so-called ‘born global’ firms also appear to differ from firms that internationalise in a more gradual, stepwise fashion. This raises interesting questions about how entrepreneurial firms acquire and manage knowledge about markets, networks and capabilities in turbulent and uncertain environments and how the values embedded in organisational cultures might influence strategic choices. The following articles in this special edition of the Journal of International Entrepreneurship focus specifically on how innovative firms—particularly small and medium-sized enterprises—recognise and exploit market opportunities, how they learn from international market entry and penetration experiences to improve core capabilities and how values may influence supply chain management and start-up decisions.     

Linking two dimensions of entrepreneurial orientation to firm performance: The moderating role of environment and industry life cycle

The term “entrepreneurial orientation” has been used to refer to the strategy-making processes and styles of firms that engage in entrepreneurial activities. A popular model of entrepreneurial orientation (EO) suggests that there are five dimensions of EO—autonomy, innovativeness, risk taking, proactiveness, and competitive aggressiveness (Lumpkin and Dess 1996). This paper reports on two of those dimensions—proactiveness and competitive aggressiveness. Proactiveness refers to how firms relate to market opportunities by seizing initiative in the marketplace; competitive aggressiveness refers to how firms react to competitive trends and demands that already exist in the marketplace. Despite these distinctions, prior research has tended to equate these two concepts and argued that they have a similar effect on firm performance. This paper investigates how these two approaches are related to each other, how they are related to performance, and how their function differs in the environments in which firms exhibit these approaches to strategy making. These distinctions are important because proactiveness and competitive aggressiveness represent distinctly different avenues to entrepreneurial success.A field study was conducted in which 124 executives from 94 firms were surveyed. These were executives from non-affiliated, non-diversified firms who were actively involved in strategic decision making at the top level of the firm. All firms reporting had at least one respondent who was an owner. Analysis of the data was conducted in two phases. In phase 1, factor analysis was used to examine the distinctions between different dimensions of EO. Proactiveness and competitive aggressiveness emerged as two separate factors indicating that these two strategy-making modes were perceived differently by the executives in the study. In the second phase, the relationship of these two dimensions to performance was analyzed in various contexts. Initial tests found that proactiveness was positively related to performance but competitive aggressiveness tended to be poorly associated with performance.Subsequent tests of the EO-performance relationship indicated that the stage of industry life cycle tended to favor one entrepreneurial orientation over another. The performance of firms in the early stages of industry development was stronger when their strategy making was proactively oriented. In contrast, a competitively aggressive frame of mind was helpful to firms in more mature stages of industry development. These findings were supported by other tests of the business environment. In dynamic environments, characterized by rapid change and uncertainty, proactive firms had higher performance relative to competitively aggressive firms. In hostile environments, where competition is intense and resources are constrained, competitively aggressive firms had stronger performance.The findings suggest that these two different approaches to entrepreneurial decision making may have different effects on firm performance. The differences were particularly apparent in the way firms relate to their external environment. Proactiveness—a response to opportunities—is an appropriate mode for firms in dynamic environments or in growth stage industries where conditions are rapidly changing and opportunities for advancement are numerous. But such environments may not favor the kind of combative posturing typical of competitive aggressiveness. Firms in hostile environments, or in mature industries where competition for customers and resources is intense, are more likely to benefit from competitive aggressiveness—a response to threats. A further implication of this research is that the dimensions of an entrepreneurial orientation, often considered to be positively related to performance under all conditions, may not always be associated with successful outcomes. This study indicates that the dimensions of EO often vary independently rather than covary, suggesting that the extent to which an entrepreneurial approach to strategy making is useful will frequently depend on the organizational or environmental conditions under which such decisions are made.     

Aligning strategic processes in pursuit of firm growth

Strategy formation mode refers to the way organizations devise their strategies. While some organizations do so through an explicit, formalized, and planned method, other organizations unintentionally create patterns in their strategic decisions—a strategy formation route that is more emergent in nature. This research explores the relationship between strategy formation mode and firm growth. Further, this article explores two strategic processes—forecasting and long-range objective setting—and their efficacy in association with particular strategy formation modes. Primary and secondary data collected from 103 manufacturing firms were used to test the hypotheses. Results indicate that the relationship between strategy formation mode and firm growth is curvilinear (inverted-U shape). Further, a three-way interactive effect is found between strategy formation mode, forecasting, and long-range objective setting on firm growth.     

Connecting big data management capabilities with employee ambidexterity in Chinese multinational enterprises through the mediation of big data value creation at the employee level

Drawing from the knowledge-based dynamic capabilities (KBDCs) view, this study examines the association of big data management capabilities with employee exploratory and exploitative activities at the individual level. Furthermore, it also investigates the mediating role of big data value creation in the association of big data management capabilities with exploratory and exploitative activities. The partial least square method was employed to analyse the hypotheses using data collected from 308 employees of 20 Chinese multinational enterprises. The existing literature gives scant attention to the role of big data management capabilities at the individual level. The main contribution of this study is that it conceptualises big data management as the ability to utilise external knowledge (generated from global users) under the resource constrained environment of an emerging economy. Furthermore, this study builds upon the existing literature on KBDC to explain big data management capabilities as antecedents to ambidexterity at the individual employee level.     

The ‘big data’ myth and the pitfalls of ‘thick data’ opportunism: on the need for a different ontology of markets and consumption

ABSTRACT

The twin pillars of big data and data analytics are rapidly transforming the institutional conditions that situate marketing research. In response, many proponents of culturalist paradigms have adopted the vernacular of ‘thick data’ to defend their vulnerable position in the marketing research field. However, thick data proselytising fails to challenge several outmoded ontological assumptions that are manifest in the big data myth and it situates socio-cultural modes of marketing thought in a counterproductive technocratic discourse. In building this argument, I first discuss the relevant historical continuities and discontinuities that have shaped the big data myth and the thick data opportunism. Next, I argue that culturally oriented marketing researchers should promote a different ontological frame— the analytics of marketplace assemblages—to address how big data, or more accurately its socio-technical infrastructure, produces new kinds of emergent and hybrid market structures, modes of social aggregation, consumption practices, and prosumptive capacities.