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This paper aims to explore how historical context influences the content and selection of rhetorical legitimation strategies. Using case study method, this paper will focus on how insurance companies and labor tried to defend their legitimacy in the context of enactment of Medicare in the USA. What factors influenced the strategic (rhetorical) decisions made by insurance companies and labor unions in their institutional work?

The study is empirically grounded in archival research, involving an analysis of over 9,000 pages of congressional hearings on Medicare covering the period 1958–1965.

The authors show that rhetorical legitimation strategies depend significantly on the specific historical circumstances in which those strategies are used. The historical context lent credibility to certain arguments and organizations are forced to decide either to challenge widely held assumptions or take advantage of them. The authors show that organizations face strong incentives to pursue the latter option. Here, both the insurance companies and labor unions tried to show that their positions were consistent with classical liberal ideology, because of high respect of classical liberal principles among different stakeholders (policymakers, voters, etc.).

It is uncertain how much the results of the study could be generalized. More information about the organizations whose use of rhetorics the authors studied could have strengthened our conclusions.

The practical relevancy of the revised paper is that the authors should not expect hegemony challenging rhetorics from organizations, which try to influence legislators (and perhaps the larger public). Perhaps (based on the findings), this kind of rhetorics is not even very effective.

The paper helps to understand better how organizations try to advance their interests and gain acceptance among the stakeholders.

In this paper, the authors show how historical context in practice influence rhetorical arguments organizations select in public debates when their goal is to influence the decision-making of their audience. In particular, the authors show how dominant ideology (or ideologies) limit the options organizations face when they are choosing their strategies and arguments. In terms of the selection of rhetorical justification strategies, the most pressing question is not the “real” broad based support of certain ideologies. Insurance company and labor union representatives clearly believed that they must emphasize liberal values (or liberal ideology) if they wanted to gain legitimacy for their positions. In existing literature, it is often assumed that historical context influence the selection of rhetorical strategies but how this in fact happens is not usually specified. The paper shows how interpretations of historical contexts (including the ideological context) in practice influence the rhetorical strategies organizations choose.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The purpose of this paper is to present a strategic management framework for a successful digital transformation (DT) roll-out aimed at enabling organisational resilience. The study aims to identify the critical areas of consideration for management to strategically approach DT in order to build resilience.

The research study is based on the 3Ps framework: (1) people (culture, capabilities, engagement and well-being), (2) processes (systems) and (3) plant (technological infrastructure and tools). The research methodology is a qualitative study comprising semi-structured in-depth interviews, conducted with industry experts in different sectors undergoing major digital disruptions such as financial services, mining, oil and gas, energy and retail.

The research findings show that the successful roll-out of an organisation’s DT is largely driven by the people elements incorporating organisational culture, workforce skills and training and employee well-being. It also highlights that it is critical for organisations to invest in technological infrastructure, once the people elements have been addressed, as they are the drivers of technology implementation.

A bigger and broader sample size can validate the elements and structure of the DT framework in South Africa.

The study’s discussion unlocks understanding about: (1) what are the key enablers for successful DT; (2) what hinders organisations from realising the value of digital investments and (3) a strategic framework for the digital roll-out.

Technology is impacting employees at both a personal and professional levels. Ensuring that DT rollouts are strategical implemented lowers the impact on technostress and strengthens resilience.

The value and practical implication of this study is that the developed strategic framework can be used by managements to enable the smooth adoption of DT toward building organisational resilience in developing countries such as South Africa with low digital maturity.

While artificial intelligence (AI) has shown its promise in assisting human decision, there exist barriers to adopting AI for decision-making. This study aims to identify barriers in the adoption of AI for automated organisational decision-making. AI plays a key role, not only by automating routine tasks but also by moving into the realm of automating decisions traditionally made by knowledge or skilled workers. The study, therefore, selected respondents who experienced the adoption of AI for decision-making.

The study applied an interpretive paradigm and conducted exploratory research through qualitative interviews with 13 senior managers in South Africa from organisations involved in AI adoption to identify potential barriers to using AI in automated decision-making processes. A thematic analysis was conducted, and AI coding of transcripts was conducted and compared to the manual thematic coding of transcripts with insights into computer vs human-generated coding. A conceptual framework was created based on the findings.

Barriers to AI adoption in decision-making include human social dynamics, restrictive regulations, creative work environments, lack of trust and transparency, dynamic business environments, loss of power and control, as well as ethical considerations.

The study uniquely applied the adaptive structuration theory (AST) model to AI decision-making adoption, illustrated the dimensions relevant to AI implementations and made recommendations to overcome barriers to AI adoption. The AST offered a deeper understanding of the dynamic interaction between technological and social dimensions.

The purpose of this paper is to analyze the process of why a Brazilian digital startup company reached unicorn status the fastest.

After the literature review, the authors conducted the questionnaire containing 13 questions used in 18 in-depth interviews conducted in the case study. Saturation point combined with the independent and in-depth analysis of the researchers is used to achieve internal and external validity. The primary data collected underwent an analytical approach, followed by a resource-based view (RBV). RBV does not deal with time. There is a gap in the literature and an opportunity here: to analyze the fastest company to become a unicorn under the RBV lens.

The case reveals that value can be found in traditional sectors, as is the case of the real estate sector. This is a case of a company in the direct home-buying space.

The contribution of this paper is both practical, with the seven lessons, and theoretical. Resources allocated to a specific context in a specific geographic region shift the attention away from the absolute value of resources to the timing of aggregating them. Thus, the contribution accounting for time is new to the RBV.

The originality lies in the analysis of the dynamics of digital businesses with exponential growth.

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

Despite the relevance of how enterprise architecture (EA) contributes to organizational performance in contemporary digital technology-driven strategic renewal, little is known about the position of EA artifacts. Therefore, this study aims to build an integrative model of EA artifact-enabled EA value supplemented with a research agenda to enhance our understanding further.

This study leveraged grounded theory techniques and a systematic review approach to develop the integrative model and research agenda.

We inductively build a model of the position of EA artifacts in EA value creation. Additionally, we elaborate a research agenda that proposes (1) an investigation of the role of an EA practice in successful strategic change, (2) an examination of how to manage EA practice value generation and (3) longitudinal research to gain insight into the evolution of value creation by EA practices.

This study presents a model of EA artifact-enabled EA value, thereby contributing to our understanding of the mechanisms, inhibitors and success factors associated with EA value. Following our model, the proposed research agenda contains future research areas to help us better understand the mechanisms and interrelatedness of EA practices in highly dynamic environments.

The human factor is the most important defense asset against cyberattacks. To ensure that the human factor stays strong, a cybersecurity culture must be established and cultivated in a company to guide the attitudes and behaviors of employees. Many cybersecurity culture frameworks exist; however, their practical application is difficult. This paper aims to demonstrate how an established framework can be applied to determine and improve the cybersecurity culture of a company.

Two surveys were conducted within eight months in the internal IT department of a global software company to analyze the cybersecurity culture and the applied improvement measures. Both surveys comprised the same 23 questions to measure cybersecurity culture according to six dimensions: cybersecurity accountability, cybersecurity commitment, cybersecurity necessity and importance, cybersecurity policy effectiveness, information usage perception and management buy-in.

Results demonstrate that cybersecurity culture maturity can be determined and improved if accurate measures are derived from the results of the survey. The first survey showed potential for improving the dimensions of cybersecurity accountability, cybersecurity commitment and cybersecurity policy effectiveness, while the second survey proved that these dimensions have been improved.

This paper proves that practical application of cybersecurity culture frameworks is possible if they are appropriately tailored to a given organization. In this regard, scientific research and practical application combine to offer real value to researchers and cybersecurity executives.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.

Hyperautomation is a technological concept whose popularity has been growing continuously since the German manufacturing industry “initiated” the Fourth Industrial Revolution (Industry 4.0), whereas, on the basis of theory, hyperautomation is a term still new and little recognized. This applies equally to scientific studies (articles, conference reports) and empirical studies (quantitative, qualitative). Therefore, this article attempts to fill definition gap that exists in the literature on management and quality sciences on the term hyperautomation.

The authors use literature review approach to identify the gaps in the existing literature on hyperautomation. They present a nominal definition of hyperautomation, discuss related issues and provide a comparative perspective between hyperautomation and automation.

The article’s findings include a precise definition of hyperautomation and the problems it raises. The authors point out that the term “hyperautomation” is still relatively new and underutilized in the management and quality sciences literature. It also compares hyperautomation to automation from several angles and emphasizes how it affects businesses, industries and other economic sectors.

Authors emphasize that in order to deploy hyperautomation successfully, enterprises must take a distributed and integrated approach.

This article addresses a gap in the management and quality sciences literature about the definition of hyperautomation. Authors give a thorough explanation of hyperautomation, along with relevant problems, useful implications and a comparison between hyperautomation versus automation.