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Emerging forms of digitalisation are placing new demands on workforce entrants around the globe. This study, catalysed by innovation programs in Ukraine and Latvia, conceptualises, measures and compares key facets of dispositional readiness of university students in two post-Soviet nations for digitalised work.

Survey data, addressing technology attitudes and personal–cultural orientations (PCO), were collected by project teams at universities in Ukraine and Latvia and delivered to the authors for analysis. The authors defined three characteristics of digitalised work, conceptually positioned five of the measured constructs as readiness factors and generated readiness profiles for the two national student cohorts. Investigation of significant differences between the groups was conducted using an Independent Samples T-Test. A composite profile was produced for comparing the overall dispositional readiness of both groups for digitalised work.

The factor-level profiles showed similar patterns of dispositional alignment and misalignment with digitalised work. For example, technology optimism and learning interest were reported by large percentages of Ukrainians and Latvians and tolerance for unstructured work by small percentages. However, significant differences were found in group levels of technology optimism, technology anxiety, ambiguity intolerance and empowered decision-making. In each case, the Ukrainian profile appeared more strongly aligned with the target.

The global digitalisation of work requires students, educators, human resource professionals and business leaders to rethink workforce readiness assessment and adapt (re)training programs. Technology enthusiasm and learning interest should be regarded as crucial measurable attitudes motivating technical skills development. Also, cultural orientations should be positioned alongside personality traits and digital skills as factors shaping successful human–computer interaction.

This study initiates a new sociotechnical and cross-cultural trajectory of technology readiness research from data generated in two post-Soviet contexts. Moreover, it positions several measurable dispositions as factors influencing student readiness for digitalised work.

Teaching and learning are being transformed by digital technology, where the present generation of students, termed millennials, are more adept with the increasingly digitalised world we live in. Following this, lecturers and institutions are adapting and adopting a blended learning model across disciplines, which now commands an entire domain of research and application. However, questions remain about how ready students are for a blended learning model of instruction. The purpose of this study is to investigate students’ readiness for blended learning in a leading Malaysian private higher education institution.

This study used a non-experimental quantitative research design. Data were gathered from a sample of 274 pre-university and undergraduate students using the blended learning readiness engagement questionnaire. Data was analysed using WINSTEPS Rasch model measurement software to determine the validity and reliability of the instrument. Descriptive statistics (mean and standard deviation) scores, (logit) value of the item and (logit) value of a person was used to examine students’ readiness for a blended learning model of instruction and specifically assess their readiness based on gender, age, ethnicity and field of study.

Findings indicate that students were ready for blended learning. Further analysis indicated there were differences in students’ readiness for blended learning based on gender, age, ethnicity and field of study.

This study provides insight into students’ readiness towards blended learning in a leading Malaysian private higher education institution, discusses implications for blended learning practices and offers recommendations for future research.

Industry 4.0 is recognised as a competitive strategy that helps implementers optimise their value chain. However, its adoption poses several challenges. This study investigates and ranks the drivers and barriers to implementing Industry 4.0 in the Thai sugar industry, the world's second-largest sugar exporter. It also evaluates the industry's readiness for Industry 4.0.

The drivers and impediments were identified based on a systematic literature review (SLR) and further investigated using a questionnaire, expert interviews, Pearson's correlation and nonparametric statistical analyses. The IMPULS model was used to assess the industry's readiness.

Most companies expect to minimise costs, develop employees and improve various elements of operational performance and data tracking capability. Thai sugar producers are still at a low readiness level to deploy Industry 4.0. High investment is the major challenge. Small businesses struggle to hire competent employees, collaborate with a highly credible technology provider and adapt to new solutions.

The findings can serve as a benchmark or guide for sugar manufacturers and companies in other sectors, where Industry 4.0 technologies are not yet widely utilised, to overcome existing roadblocks and make strategic decisions. They can also assist governments in developing policies that foster digital transformation and increase national competitiveness.

There is a scarcity of research on Industry 4.0 execution in the sugar industry. This study addresses this gap by investigating the reasons for the hesitancy of sugar producers to pursue Industry 4.0 and proposing solutions.

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

Organizations use Industry 4.0 readiness models to evaluate their preparedness prior to the implementation of Industry 4.0. Though there are many studies on Industry 4.0 readiness models, the dimensions of readiness differ. Besides, there is no study empirically validating the readiness model in different sectors or types of organization. The purpose of this study is to conceptualize the dimensions of the Industry 4.0 readiness model and subsequently evaluate the criticality of these dimensions in manufacturing, service, small and medium-sized enterprises (SMEs) and large enterprises (LEs).

The study uses an exploratory sequential mixed method design. In phase one, 37 senior managers participated through a purposive sampling frame. In phase two, 70 senior managers participated in an online survey.

The results of the study indicated that the Industry 4.0 readiness model has 10 dimensions. Further, the criticality of the dimensions as applied to different sectors and type of organizations is put forward. This study will help manufacturing, services, SMEs and LEs to evaluate Industry 4.0 readiness before commencing the deployment of Industry 4.0.

The findings can be very beneficial for Industry 4.0 practitioners and senior managers in different organisations to understand what readiness dimensions need to be considered prior to implementation of Industry 4.0 technology.

This paper makes an attempt to conceptualize the Industry 4.0 readiness model and utilizes an exploratory mixed method for critically evaluating the dimensions related to the model.

The purpose of this study is to investigate how professionals learn from varying experiences with errors in health-care digitalization and develop and use negative knowledge and digital ignorance in efforts to improve digitalized health care.

A two-year qualitative field study was conducted in the context of a public health-care organization working with digital patient communication. The data consisted of participant observation, semistructured interviews and document data. Inductive coding and a theoretically informed generation of themes were applied.

The findings show that both health-care and digital communication professionals learn through experiences with digital “rule-” and “knowledge-based” errors in patient communication and develop negative knowledge and awareness of digital ignorance. In their joint efforts, they use negative knowledge to “bend the rules” and to explore digital ignorance in efforts to improve patient communication.

This study provides insight into the importance of collaboration between professionals with varying experience of errors in digitalizing patient communication. Such collaboration is required to acknowledge own shortcomings and create complementary negative knowledge to improve digital patient communication. This is particularly important when working with innovative digitalization in health care.

The purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.

The factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).

The prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.

Indian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.

The novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.

The purpose of this paper is to illustrate how a newly constructed organization behavioral lens for participative action research (PAR) may aid a public-sector organization in successfully digitalizing its internal shared services. In addition, the intervention is aimed at fostering a continuously improving type of learning culture on the workfloor of a new service unit.

In a large Dutch municipality, the installation of a new digitalized process of offering internal services was studied. A PAR method, the so-called Fourth Generation Evaluation, was used on seven internal actor groups. This method enables various intra-organizational actors to reflect collectively on the ongoing change progress. Their explicit views on the change were communicated to all actors and the change agents.

The study describes the attempt of establishing a continuously improving learning culture during an internal digitalization process: substantial participation of the non-managerial employees was enabled. The paper highlights the practical value of the internal digitalization approach used, and concludes with four change process lessons learnt for those wanting to initiate a continuously improving culture on the workfloor.

Even though the findings are based on one case, they may be of interest to other public/private organizations aiming to establish a continuously improving culture within workfloor units that interact, on a daily basis, with (internal) customers.

The paper offers a theoretical framework and a matching practical approach to the process of creating an internal shared service unit that aims to evolve further into a customer-oriented, continuously improving culture.

Family businesses often lack sufficient knowledge about digital business model innovation digital business model innovation (BMI). This study's purpose was to analyze how and when organizational readiness for digital innovation exerts a positive impact on family businesses' digital BMI. To do so, the authors examined the mediating effect of the familiness learning mechanism and the moderating effect of family involvement on this relationship.

A quantitative survey method was used to collect the data for this study. Using a sample of 282 family businesses involved in manufacturing in China, the authors conducted hierarchical regression analyses to evaluate the authors' theoretical model.

The results of this work demonstrate a positive relationship between organizational readiness for digital innovation and family businesses' digital BMI, and the find that the familiness learning mechanism mediates this relationship. The findings also show that second-generation family involvement in management moderates the direct effect of organizational readiness for digital innovation on the familiness learning mechanism, as well as the indirect effect of organizational readiness for digital innovation on digital BMI via the familiness learning mechanism. Moreover, the results establish that family involvement in ownership moderates the direct effect of the familiness learning mechanism on digital BMI, as well as the indirect effect of organizational readiness for digital innovation on digital BMI via the familiness learning mechanism.

This study provides practical contributions to the literature on family businesses and to public policy, providing concrete suggestions for fostering digital innovation in family enterprises. This study also enriches our understanding of the unique conditions by which family businesses can successfully implement digital BMI.

This research confirms that organizational readiness for digital innovation is an antecedent of digital BMI. This finding offers a new perspective that helps explain what might lead family businesses to engage in digital BMI. This study also places the familiness learning mechanism into a theoretical framework, which expands the current understanding of how organizational readiness for digital innovation facilitates digital BMI. Moreover, this work provides new insights into the boundary conditions by which organizational readiness for digital innovation affects the digital BMI of family businesses in terms of second-generation family involvement in management and family involvement in ownership.