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Data quality metadata (DQM) is a set of quality measurements associated with the data. Prior research in data quality has shown that DQM improves decision performance. The same research has also shown that DQM overloads the cognitive capacity of decision-makers. Visualization is a proven technique to reduce cognitive overload in decision-making. This paper aims to describe a prototype decision support system with a visual interface and examine its efficacy in reducing cognitive overload in the context of decision-making with DQM.

The authors describe the salient features of the prototype and following the design science paradigm, this paper evaluates its usefulness using an experimental setting.

The authors find that the interface not only reduced perceived mental demand but also improved decision performance despite added task complexity due to the presence of DQM.

A drawback of this study is the sample size. With a sample size of 51, the power of the model to draw conclusions is weakened.

In today’s decision environments, decision-makers deal with extraordinary volumes of data the quality of which is unknown or not determinable with any certainty. The interface and its evaluation offer insights into the design of decision support systems that reduce the complexity of the data and facilitate the integration of DQM into the decision tasks.

To the best of my knowledge, this is the only research to build and evaluate a decision-support prototype for structured decision-making with DQM.

To compete in the current digital economy, organizations need a workforce capable of developing novel products/services using digital technologies to create value. The purpose of this study is to explore and understand the antecedents of digital innovativeness so that we can appropriately train the workforce.

The authors theorize a model linking four individual characteristics (entrepreneurial orientation, digital literacy, entrepreneurial self-efficacy and digital technology self-efficacy) to digital innovativeness. They frame four hypotheses and validate them using a survey.

This study reveals that two antecedents of individual digital innovativeness linked to personal beliefs of competency are correlated to an individual's digital innovativeness. It also challenges long-held assumptions in technology education and industry by revealing that two other factors typically associated with digital innovativeness – basic digital literacy and entrepreneurial orientation – do not relate to the individual's digital innovativeness.

We believe that the study is the first of its kind to examine the antecedents of digital innovativeness with an eye on the characteristics necessary to innovate with digital technologies to create value. By hiring employees exhibiting high levels of these characteristics, promoting a culture of experimentation and educating its workforce to gain confidence in its abilities to execute and deploy digital technologies, organizations can secure their strategic position in a business landscape driven by digital innovations.

Digital platforms for the provision of food information-based services (FISs) represent a consolidated business with increasing revenue streams for entrepreneurs. Such platforms have transformed and clarified the nature of uncertainty and ambiguity inherent in the traditional food sector entrepreneurial processes. Anyway, a clear understanding of the value of digital platforms for FISs is not yet consolidated in the literature. With this paper, the authors try to fill this gap through a critical literature review of scientific research that combines knowledge on food consumer's behavior and user's knowledge behavior.

The authors carried out a critical literature review of scientific research combining knowledge of food consumer's and food information user's behavior. This allowed the identification of the main value components of FISs.

The authors propose a multidimensional framework for modelling the value proposition of digital platforms for FISs. Three main value dimensions have been identified: relevance, credibility, and accessibility. These dimensions concur with the consumer's perceived value of consumers in terms of benefits increase and cost reduction.

The research was intended to shed light on aspects characterizing consumers' perception of food information value. The authors put in evidence that the informational perspective of food communication is under-investigated. This study attempts to provide a holistic overview of the dimensions impacting on consumers' perception of the value of information for food consumers, opening new research perspectives.

The framework represents a tool for positioning food information offerings on the market, with the objective to analyze the value proposition of FISs according to a consumer perspective and to understand gaps of current offering of FISs. Moreover, it may support the design of a new generation of digital platform for food information provision, which would respond to consumers' expectations and information needs, highlighting emerging business opportunities for digital entrepreneurs.

Few research works provide a characterization of value proposition of digital platforms providing food information to consumers. In particular, to date, literature lacks of a holistic overview of the dimensions influencing consumer's perception of the information value of food communications.

Numerous data quality (DQ) definitions in the form of sets of DQ dimensions are found in the literature. The great differences across such DQ classifications (DQCs) imply a lack of clarity about what DQ is. For an improved foundation for future research, this paper aims to clarify the ways in which DQCs differ and provide guidelines for dealing with this variance.

A literature review identifies DQCs in conference and journal articles, which are analyzed to reveal the types of differences across these. On this basis, guidelines for future research are developed.

The literature review found 110 unique DQCs in journals and conference articles. The analysis of these articles identified seven distinct types of differences across DQCs. This gave rise to the development of seven guidelines for future DQ research.

By identifying differences across DQCs and providing a set of guidelines, this paper may promote that future research, to a greater extent, will converge around common understandings of DQ.

Awareness of the identified types of differences across DQCs may support managers when planning and conducting DQ improvement projects.

The literature review did not identify articles, which, based on systematic searches, identify and analyze existing DQCs. Thus, this paper provides new knowledge on the variance across DQCs, as well as guidelines for addressing this.

Information technology (IT) personnels’ technical, business and behavioral skills are critical enablers for generating IT value. In an increasingly digitalized working environment where non-IT employees participate in digital innovations, a focus on IT personnels’ skills only doesn’t meet researchers’ need for a framework to study digital skills and managers’ need to address digital skills challenges across an enterprise’s workforce. Nevertheless, the digital skills topic is complicated by conceptual ambiguity and a lack of theoretically derived and empirically validated model. The purpose of this study is to address this problem.

Theoretically, this study draws on human capital (HC) and resource-based view (RBV) theories. Empirically, it follows mixed method combining interviews and a survey.

The digital skills construct is a multidimensional second order reflective construct. While its development is influenced by an organization’s commitment and exposure to digitalization, it influences the value organizations obtain from digitalization.

This study conceptualizes the digital skills construct, identifying technology agnostic subdimensions that are meaningful beyond a particular digital domain [information and communication technology (ICT), information, Internet, Inter of Things (IoT)] and establishing a valid measure. Other researchers can improve both the indicators of the existing four conceptually distinct and managerially recognizable workplace digital skills dimensions as well as testing new ones.

Managers can use the instrument to assess the extent to which their non-IT workforces are equipped with digital skills and get strategic insights for specific interventions such as upskilling or buying in skills.

The main theoretical contribution of the paper is the conceptualization and validation of the digital skills construct for the non-IT workforce. Furthermore, we provide a theoretical framework to explain the factors that could influence the development of digital skills and demonstrate the impact that digital skills have on selected digitalization value indicators. This contribution provides the foundation for investigating the drivers, outcomes and the relationship of digital skills to other constructs such as digital transformation, innovation and firm performance.

Micro and small enterprises (MSE) play a critical role in the Swiss economy but had no meaningfully adopted working from home (WFH) policy before the COVID-19 crisis. The timing of the study’s data collection allowed a unique assessment of Swiss MSEs’ adoption of WFH enabled by the adoption of digital technologies due to the first government-mandated COVID-19 lockdown. The study also set out to assess the permanence of any changes in the adoption of WFH by MSEs after initial government COVID-19 restrictions ended.

The study uses a threefold theoretical framework combining social, technical and spatial dimensions. Data were collected via telephone interviews. The utilised sampling frame included 153,000 small businesses with 4–49 employees, and the realised sample for the study was 503 interviews with MSE owners and managing directors (MDs).

The Swiss government’s COVID-19 crisis lockdown policies accelerated the digital transformation of work by employees in Swiss MSEs by increasing the number of employees WFH. However, the number of MSEs with WFH employees decreased after the first lockdown ended. Small business leadership is an important influence on the persistence of any increases in WFH.

The data collection uniquely captures the effects of externally driven digital transformation of work in small businesses by the adoption of WFH. The findings show that small businesses can rapidly learn new ways of working and support the claim that Swiss MSE MDs play a critical role in the adoption of WFH. They also confirm the importance of digital leadership and culture for realising the potential of WFH in small businesses.

Digital technology changes the organizational structure of traditional firms, creating opportunities for entrepreneurship. These modifications are known as “digital transformation” (DT). In addition, higher education institutions (HEIs) are altering the form of student–lecturer and teaching–learning interaction, where DT restructures the bases of soft skills (SS). Since SS are difficult to measure, this study aims to analyze the bases of SS for digital academic entrepreneurship, responding to the following research question: What are the bases of digital academic entrepreneurship and how are they formed?

An extensive integrative review of the literature revealed that due to the editable, re-combinable, reprogrammable and generating nature of digital technology, the basis of DT, it is necessary to develop SS in higher education students.

The results show that the competencies can be developed considering three major groupings: (1) individual characteristics, (2) cultural characteristics and (3) knowledge sharing.

Since SS are not easily taught, this study shows how the use of digital tools can help and support this type of process. It is suggested, therefore, that those in charge of HEIs should use the pillars presented in the framework proposed here to guide their institutions' strategic planning. With these pillars in mind, the aim is to stimulate an entrepreneurial mentality in students and develop digital academic entrepreneurship.

An innovative conceptual model of digital academic entrepreneurship is proposed from the perspective of SS, where the interlinking of those groupings is permeated by DT, as well as the disruptive role of digital technology, leading to the development of an entrepreneurial mentality in HEI students.

This study aims to analyse the influence of the pillars (hard and soft skills) of digital academic entrepreneurship on students' entrepreneurial intention.

This was done by adopting a quantitative methodology involving empirical research with a sample of 761 university students from two countries and adopting structural equation analysis to validate the theoretical model proposed.

The results indicate a direct influence between hard and soft skills and entrepreneurial intention, and a positive, indirect influence between these and entrepreneurial intention mediated by the dimensions of the theory of planned behaviour (TPB) – entrepreneurial attitude, subjective norms and perceived behavioural control. Therefore, the pillars of digital academic entrepreneurship have a direct and indirect influence on university students' entrepreneurial intention.

This study also contributes to better operationalization of entrepreneurial education in university environments, since the development of hard and soft skills can be planned better based on the model proposed here. Considering the relations between the dimensions of hard and soft skills and those of TPB, this study shows there can be an influence on students' entrepreneurial intention.

In this study, a new and innovative construct is inserted in the model of entrepreneurial intention: “structural pillars of digital academic entrepreneurship” through structural equation modelling, to determine the degree of influence of these pillars (hard and soft skills) constructs on HEI students' entrepreneurial intention.

This study aims to systematically map the state of work on human–machine collaboration in organizations using bibliometric analysis.

The authors used a systematic literature review to survey 111 articles on human–machine collaboration published in leading journals to categorize the theories used and to construct a framework of human–machine collaboration in organizations. A bibliometric analysis is applied to statistically evaluate the published materials and measure the influence of the publications using co-citation, coupling and keyword analyses.

The results inform that the research on human–machine collaboration in the organizational field is targeted at four aspects: performance, innovation, human resource management and information technology (IT).

This work is the first exploratory piece to assess the extent and depth of research on human–machine collaboration.

The purpose of this paper is to develop data quality (DQ) assessment model based on content analysis and metadata analysis.

A literature review of DQ assessment models has been conducted. A study of DQ key performances (KPIs) has been done. Finally, the proposed model has been developed and applied in a case study.

The results of this study shows that the metadata data have important information about DQ in a database and can be used to assess DQ to provide decision support for decision makers.

There is a lot of DQ assessment in the literature; however, metadata are not considered in these models. The model developed in this study is based on metadata in addition to the content analysis, to find a quantitative DQ assessment.