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This study aims to explore the alignment between strategic plans of the Portuguese public higher education institutions (HEIs) and their perception of the integration of sustainability in education and curricula.

The strategic plans from 15 institutions were selected for content analysis; data about the integration of sustainability in education and curricula, from these HEI, were collected with an online questionnaire (self-report survey). Qualitative and quantitative analyses were performed.

Strategic plans of the Portuguese public HEIs seem to not be sufficiently aligned with self-assessment integration of sustainability in education and curricula.

The classifications used in the content analysis were constructed and revised by the authors to reduce coder interpretation issues and subsequent bias in the results. However, some subjectivity could remain. The analysis of strategic plans and self-report surveys answered by top management, or a technician, does not assess the practices and sustainability implementation in education and curricula.

This study allows the self-report of already-implemented practices to be compared to the planned strategy of HEI governance in Portugal as stated in their strategic plans.

An analysis and respective insights on the lack of connection between strategic planning and self-report practices about sustainability implementation, using Portugal as a case study.

Testing business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.

The methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.

Results of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.

The databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.

Three main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.

The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work.

This study was conducted by using a qualitative critical incident technique-inspired questionnaire.

The findings suggest that workers in the software industry perceive that the most obvious obstacles to experiencing flow are related to work not presenting enough cognitive challenges and situational barriers related to the characteristics of the job (e.g. workdays having too many interruptions and distractions, timetables often being considered too tight for creative exploration and problem solving and having negative user experiences with development tools).

The findings provide insights into flow barriers, specifically barriers that prevent workers in the software industry from experiencing flow.

Business models are increasingly recognized as a concept to support innovation in organizations. The implementation and operation of a new or altered business model involves the (re-)design of an organization's business processes and their successful execution. This study reviews and synthesizes the existing body of literature to guide organizations in systematically moving from a business model design to the implementation and operation of the business model through their underlying business processes.

A systematic literature review of the methods that bridge business models and business processes is performed. The selected 34 studies are classified according to the method's characteristics and the support in the design, implementation and operation of business models.

The results of the systematic review provide an overview of existing methods that organizations can adopt when moving from business model design into the implementation and operation of their business model using processes.

This work provides a comprehensive overview and detailed insight into the existing methods that align business models and business processes. It increases the understanding on how these two concepts can be synthesized to support more effective digital innovation in organizations. Based on the review results, knowledge gaps are identified and an agenda for future research bridging the fields of business models and business processes is proposed.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.

A discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.

Numerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.

Practically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.

As a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.

Digital servitization concerns how manufacturers utilize digital technologies to enhance their provision of services. Although digital servitization requires that manufacturers possess new capabilities, in contrast to strategic (or dynamic) capabilities, little is known about how they develop the required operational capabilities. The paper investigates the mechanisms for developing operational capabilities in digital servitization.

This paper presents an exploratory study based on 15 large manufacturers operating in Europe engaged in digital servitization.

Three operational capability development mechanisms are set out that manufacturers use to facilitate digital servitization: learning (developing capabilities in-house), building (bringing the requisite capabilities into the manufacturer), and acquiring (utilizing the capabilities of other actors). These mechanisms emphasize exploitation and exploration efforts within manufacturers and in collaborations with upstream and downstream partners. The findings demonstrate the need to combine these mechanisms for digital servitization according to combinations that match each manufacturer’s traditional servitization phase: (1) initial phase - building and acquiring, (2) middle phase - learning, building and acquiring, and (3) advanced phase - learning and building.

This study reveals three operational capability development mechanisms, highlighting the parallel use of these mechanisms for digital servitization. It provides a holistic understanding of operational capability development mechanisms used by manufacturers by combining three theoretical perspectives (organizational learning, absorptive capacity, and network perspectives). The paper demonstrates that digital servitization requires the significant application of building and acquiring mechanisms to develop the requisite operational capabilities.

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations.

This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in three-step iterations to understand reflexive practice when using software development models.

The study shows how work processes are based on team members’ experiences and common views. This study highlights the challenges of organizational learning in system development projects. Current practice is unreflective, habitual and lacks systematic ways to address recurring problems and share information within and between organizations. Learning is episodic and sporadic. Knowledge from previous experience is individual not organizational.

Software development teams and organizations tend to learn about, and adopt, software development models episodically. This research expands understanding of how organizational learning takes place within and between organizations with practitioners who participate in teams. Learnings show the potential for further research to determine how new curriculums might be formed for teaching software development model improvements.