Purpose: This paper aims to bring together the existing theory from knowledge management (KM), competitive intelligence (CI) and big data analytics to develop a more comprehensive view of the full range of intangible assets (data, information, knowledge and intelligence). By doing so, the interactions of the intangibles are better understood and recommendations can be made for the appropriate structure of big data systems in different circumstances. Metrics are also applied to illustrate how one can identify and understand what these different circumstances might look like. Design/methodology/approach: The approach is chiefly conceptual, combining theory from multiple disciplines enhanced with practical applications. Illustrative data drawn from other empirical work are applied to illustrate some concepts. Findings: Theory suggests that the KM theory is particularly useful in guiding big data system installations that focus primarily on the transfer of data/information. For big data systems focused on analytical insights, the CI theory might be a better match, as the system structures are actually quite similar. Practical implications: Though the guidelines are general, practitioners should be able to evaluate their own situations and perhaps make better decisions about the direction of their big data systems. One can make the case that all the disciplines have something to add to improving how intangibles are deployed and applied and that improving coordination between KM and analytics/intelligence functions will help all intangibles systems to work more effectively. Originality/value: To the authors’ knowledge, very few scholars work in this area, at the intersection of multiple types of intangible assets. The metrics are unique, especially in their scale and attachment to theory, allowing insights that provide more clarity to scholars and practical direction to industry.

The study looks at developing a person-organization fit model based on the unique characteristics of the new generational cohort, Generation Z, now entering the workforce. Theory suggests competitive advantage may come to a firm based on its unique human capital, the human resources it employs and develops. Further, organizations will be more successful in attracting the valuable employees they seek if they can provide a workplace appealing to them in terms of organizational values, culture, and other aspects that may also include more familiar enticements such as pay and benefits. To address the gap, this pioneering study investigates the context of person-organizational culture for the Z Generation entering the labor market. The key questions answered by the authors when describing the Person-Organization Fit Framework for Generation Z include the differences in how organizational culture appeals to Gen Z men and Gen Z women. The research results are presented in three steps: an analysis of workplace environment elements for Gen Z, correlation analysis between the workplace environment elements required by Gen Z, and presentation of a Person-Organization Fit Framework for Gen Z. From a sample of 3393 students at technological secondary schools in the Wielkopolska Region, the survey results provided evidence of the workplace preferences for this cohort. In addition, results were further analyzed for differences in gender and intended profession. For this region, Generation Z has variable individual needs and wants, some of which can be easily identified (gender, profession) but some of which may be less clear. These research results may be used for designing appealing workplaces taking into account person-organization needs for young people. Based on this novel research, organizations employing the resulting work framework for Gen Z will be better prepared to consider the nature and communication of what they have to offer as well as how they can be flexible in adapting these offerings to unique individuals.

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).

A standard prescription for industry is increased investment in and application of intangible assets, including knowledge management, competitive intelligence, and, now, big data. This paper examines whether a more measured, strategic approach might be appropriate, particularly whether knowledge development and protection needs vary by type of industry. Overall, knowledge decisions should be more strategic, there are some patterns in type of industry (services) and type of knowledge. In developing this case for a more strategic approach to developing and protecting knowledge assets, this paper applies concepts from the fields of knowledge management, intellectual capital, and competitive intelligence to healthcare industries. The literature is scanned to develop a categorization of the competitive conditions facing firms in these industries. This categorization (a Strategic Protection Factor framework) identifies the degree of knowledge development in an industry as well as the level of competitive intelligence activity and resulting knowledge protection concerns. Assigning data reflecting these variables, knowledge development and knowledge protection, the paper assesses the competitive circumstances surrounding 10 healthcare industries and provides broad strategic recommendations. The results show that knowledge development and knowledge protection conditions vary dramatically, even within a specific realm such as healthcare. Similarly, when looking at service and non-service healthcare industries, the same conclusion is apparent, with widely varying competitive conditions. The results call for a much more strategic, circumstance-specific approach to decisions concerning knowledge in organizations as well as more scholarly work on the differing conditions within which knowledge management takes place as well as where and why they exist.