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The purpose of this paper is to provide guidance for designing and generating cumulative knowledge based on qualitative research.

The paper draws on the philosophy of science and specific examples of qualitative studies in accounting that have claimed a cumulative contribution to knowledge to develop a taxonomy of theoretically justified approaches to generating cumulative knowledge from qualitative research.

The paper argues for a definition of cumulative knowledge that is inclusive of anti-realist research, i.e. knowledge is cumulative if it increases the extent and density of intertextual linkages in a field. It identifies the possibility of cumulative qualitative research based on extensions to the scope of the knowledge and the depth of the knowledge. Extensions to the scope of the knowledge may include expanding the time periods, context, and/or theoretical perspective used to explore a phenomenon. Extensions to the depth of the knowledge may include new empirical knowledge, methodological pluralism, theory elaboration, or analytic generalization. Individual studies can demonstrate their contribution to cumulative knowledge by locating their research within a typology/taxonomy that makes explicit the relationship of current research to past, and potential, research.

The taxonomy may be useful to qualitative researchers designing and reporting research that will have impact on the literature.

The increased use of research impact as an evaluation metric has the potential to handicap the development qualitative research which is often thought of as generating non-cumulative knowledge. The taxonomy and the strategies for establishing cumulative impact may provide a means for this approach to research to establish its importance as a contribution to knowledge.

The concept of cumulative knowledge has not been systematically applied to research based on qualitative methods.

The purpose of this paper is to investigate the combined effects of different modalities of long-term knowledge accumulation and short-term knowledge searching on the generation of high-impact ideas. The authors aim at providing useful conclusions for academic scholars.

Two dimensions of the cumulative knowledge structures of researchers are measured: knowledge depth and knowledge breadth. The search strategies employed by researchers are classified as local search and distant search. The authors use researchers’ historical publications to measure cumulative knowledge structures. References contained in these publications serve as an indicator of knowledge searching behaviors and are used to measure search strategies. Highly cited papers with random-but-matched papers from the same journal published in the same year are adopted to test the hypotheses.

The knowledge depth of researchers positively predicts the generation of high-impact ideas. Knowledge breadth has a bell-shaped relationship to the generation of high-impact ideas. Two instances of “strategic fit” between the knowledge structures and search strategies of researchers are identified; namely, knowledge breadth combines most effectively with local search, and knowledge depth combines most effectively with distant search in generating high-impact ideas.

Using article references to measure authors’ knowledge search behaviors may lead to biases. Future research should perform a survey to obtain a comprehensive understanding of the knowledge search behaviors of scholars.

A “T-shaped” knowledge structure in the long run is recommended for maximal generation of high-impact ideas. Researchers who have not adopted this optimal knowledge structure can employ a matched search strategy to leverage their existing knowledge structures.

This paper is among the first to examine the interactive effects between the cumulative knowledge structures and short-term knowledge searching strategies of researchers. The authors have enriched the exploration and exploitation theory by adding the dimension of time into the analysis.

Due to its technical focus, the introductory accounting course has a hierarchical knowledge structure that requires students to master and integrate abstract knowledge which builds on itself over time. The purpose of this paper is to explore the relationship between engagement and examination performance for students enrolled in a hierarchically structured course.

This research involves a retrospective study of an introduction to accounting course examining the relationship between increased engagement and examination performance. Students are provided opportunities for engagement through assigned homework and optional ungraded assignments. Performance is measured by scores on each of three examinations conducted throughout the semester.

The study finds that additional engagement in assignments has no significant impact on mid-semester examination performance; however, sustained engagement throughout the semester has a cumulative impact on final examination performance. Moreover, students that perform well on mid-semester examinations do not benefit from additional engagement, whereas students that perform poorly on the mid-semester examinations exhibit substantially higher final examination scores from sustained engagement.

This study illustrates the complex interplay between engagement and performance and the timing of performance gains. The implication for educators is that increased sustained engagement is likely to result in increased but delayed student performance gains in disciplines with hierarchical knowledge structures.

This study contributes to the literature in its examination of the timing of performance benefits gained from increased engagement in courses with a cumulative knowledge base.

In this chapter we ask a simple question: how can we tell if strategic management research is making progress? While other limitations are noted, we argue that it is the absence of metrics for gauging research progress that is most limiting. We propose that research should focus on measures of effect size and that “precision” and “generalizability” in our predictions of important phenomena represent the core metrics that should be used to judge whether progress is occurring. We then discuss how to employ these metrics and examine why existing research practices are likely to hinder efforts to develop cumulative knowledge.

Knowledge is a strategic resource for firms and it can enable them to achieve competitive advantage. Large companies engaged in internationalization pay particular attention to knowledge as a source of innovation. The purpose of this paper is to investigate current debates in the field: the first is about cumulative vs composite knowledge; the second concerns the degree of diversity and redundancy in knowledge-based dynamics; and the third debate is about incremental vs radical innovation.

The authors have used an inductive approach to perform a longitudinal case study of multinational corporation-semiconductor (MNC-SC). Total of 13 interviews were conducted over a four-year period. The MNC-SC case study has given the opportunity to analyse knowledge resources, knowledge, and innovation processes in a context of internationalization.

The findings indicate that in order to achieve technological innovation in a context of internationalization, the company builds knowledge in a cumulative fashion, which can create a path dependency problem. To ensure complementarity between cross-functional teams located long distances from one another, and maximize the utilization of resources, MNC-SC must establish common standards. To maximize returns from composite knowledge, in a context of internationalization, knowledge diversity is preferable over redundancy. However, true knowledge transfer, sharing, and learning are limited. Combinatorial and incremental innovation through internationalization is a process based on trial and error; it maximizes technological performance and enables the company to fulfil needs without diverging from the technological trajectory of the SC industry.

The internationalization process revealed limitations: limited understanding of the content of each knowledge module, competency traps, limited innovativeness, and therefore limited wealth creation.

This paper aims to analyze the extent to which the influence of external knowledge search on innovation performance is contingent on both a firm’s innovation strategy and the industry context in which it operates.

The paper adopts a contingent approach that centers analysis on the influence of situational factors, either exogenous or endogenous to the organization, as determinants of the external knowledge search in promoting the firm’s innovation performance. The empirical study is based on a large sample of 18,955 firms operating in 29 industries that belong to 13 European countries.

This analysis reveals that a broad knowledge search is more effective for firms that innovate in new goods, while a deeper knowledge search is more effective for firms that innovate in new services. The results of this study also indicate that external knowledge search varies across industries, with search depth being used more in industries in which the knowledge development process is cumulative and appropriable, while the external breadth search is preferred in industries with a high level of technological opportunity.

The current approach implies recognizing that the knowledge search strategies may not always be effective, and that firms should align the search strategy to both internal and external factors. Analyzing the influence of these factors can help managers to better choose the type of knowledge search (e.g. intensive or extensive search) that best aligns with the firm’s innovation objectives.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

Global competition has pushed firms to improve and upgrade their manufacturing operations continuously. Explores the role of knowledge base and learning to facilitate this phenomenon. Developing a knowledge base requires organising knowledge and expertise for a field of inquiry and making it available in formats suitable for users to support and aid various operational, developmental, and organisational functions. Classification and coding form the basis for organising knowledge bases. Classification implies grouping objects into similar classes on the basis of some similarity criteria pertinent to one or more attributes. Learning in the context of classification implies discovering new attributes, bases for grouping and requires frequent updating of the knowledge base. A formal knowledge base makes a firm’s knowledge cumulative and serves an important integrating and coordinating role for the organisation. Presents an example application utilizing classification as a tool for knowledge acquisition in design support activities.

As cyber-attacks continue to grow, organisations adopting the internet-of-things (IoT) have continued to react to security concerns that threaten their businesses within the current highly competitive environment. Many recorded industrial cyber-attacks have successfully beaten technical security solutions by exploiting human-factor vulnerabilities related to security knowledge and skills and manipulating human elements into inadvertently conveying access to critical industrial assets. Knowledge and skill capabilities contribute to human analytical proficiencies for enhanced cybersecurity readiness. Thus, a human-factored security endeavour is required to investigate the capabilities of the human constituents (workforce) to appropriately recognise and respond to cyber intrusion events within the industrial control system (ICS) environment.

A quantitative approach (statistical analysis) is adopted to provide an approach to quantify the potential cybersecurity capability aptitudes of industrial human actors, identify the least security-capable workforce in the operational domain with the greatest susceptibility likelihood to cyber-attacks (i.e. weakest link) and guide the enhancement of security assurance. To support these objectives, a Human-factored Cyber Security Capability Evaluation approach is presented using conceptual analysis techniques.

Using a test scenario, the approach demonstrates the capacity to proffer an efficient evaluation of workforce security knowledge and skills capabilities and the identification of weakest link in the workforce.

The approach can enable organisations to gain better workforce security perspectives like security-consciousness, alertness and response aptitudes, thus guiding organisations into adopting strategic means of appropriating security remediation outlines, scopes and resources without undue wastes or redundancies.

This paper demonstrates originality by providing a framework and computational approach for characterising and quantify human-factor security capabilities based on security knowledge and security skills. It also supports the identification of potential security weakest links amongst an evaluated industrial workforce (human agents), some key security susceptibility areas and relevant control interventions. The model and validation results demonstrate the application of action research. This paper demonstrates originality by illustrating how action research can be applied within socio-technical dimensions to solve recurrent and dynamic problems related to industrial environment cyber security improvement. It provides value by demonstrating how theoretical security knowledge (awareness) and practical security skills can help resolve cyber security response and control uncertainties within industrial organisations.

This paper aims to draw on a knowledge-based view to emphasize that internal technological and market knowledge is critical to developing absorptive capacity.

This is a conceptual paper, which draws on recent transformations of management practices. Thus, the paper builds on prior academic contributions.

Firms increasingly establish innovation processes that involve an active acquisition of external technologies, often through alliances and licensing. To explain differences across firms in external knowledge acquisition, marketing and product innovation researchers have recently adopted a process perspective of absorptive capacity, which refers to a firm’s ability to explore, retain and exploit external knowledge. This paper develops a conceptual framework with propositions relating technology orientation, responsive market orientation and proactive market orientation to the three process stages of absorptive capacity under different conditions of environmental dynamism.

Beyond the relevance of technology and market orientation for fostering internal innovation, this paper points to their importance for successfully acquiring external technological knowledge. In light of increasingly open innovation processes, absorptive capacity is an essential complement to internal innovation in linking technology and market orientation to firm performance.