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Digital start-ups have limited resources. With the demands of rapid growth, digital start-ups need to rely on their ability to explore external knowledge and exploit it into swift innovation. Developing absorptive capacity is an alternative to overcome this difficulty. This study aims to demonstrate how the potential and realized an increase in absorptive capacity enables organizations to innovate moderated by structural ambidexterity. Empirical evidence places more emphasis on the impact of absorptive capacity on innovation but still leaves the “black-box” question of innovation and how potential absorptive capacity (PACAP) can achieve realized absorptive capacity (RACAP).

This study tests, with a structural equation model, samples collected from 143 digital start-ups in Indonesia.

The finding of this study suggests that PACAP influences the ability to innovate only if RACAP mediates it and structural ambidexterity positively moderates the relationship between these two variables.

First, this study uses digital start-up organizations as respondents. Second, this study explores the role of the structural ambidexterity that moderates the relationship between PACAP and RACAP manifested in digital start-ups organizations that are identical to temporary companies with limited resources. Third, digital start-ups have a fast-growth life cycle, unlike regular companies. Finally, the validated scale is based on data collected entirely from digital start-ups located in Indonesia, which may limit the generalizability of the findings to other industry contexts.

Start-ups suffer from the ability to innovate that increases their propensity to fail. They overcome this failure by increasing the absorptive capacity of the founding team to improve their ability to innovate. Because of limited resources available at digital start-ups, the flexibility of their management style can overcome these barriers, allowing the pursuit of both knowledge exploration and exploitation in a balanced way.

Most of the studies explained that the ability to innovate comes from absorptive capacity. In fact, they do not explore PACAP and RACAP and their relationships. Moreover, the studies also indicated that the contextual ambidexterity moderated PACAP and RACAP. Meanwhile, digital start-ups in this study revealed that structural ambidexterity with two dimensions, i.e. shared value, and behavioral integration, enables and positively moderates the relationship between PACAP and RACAP.

The creation of positive social change (PSC) is considered the primary success criterion when evaluating social enterprise performance. However, despite a proliferation of PSC-measurements, their empirical validity and applicability in emerging economies remain largely unclear. The quantitative study examines the validity of the PSC-measurement approaches proposed by Bloom and Smith (2010; Bloom and Smith approach [BSA]) and Weaver (2020b; Weaver approach [WA]) in South Africa.

Investigating a representative sample of 347 social entrepreneurs from Gauteng and Limpopo provinces, the authors use questionnaire data to explore the factorial, convergent and discriminant validity of both PSC-measurement approaches. Statistically, this is done by applying factorial and correlation analyses.

The results yield acknowledgeable differences. BSA has a high factorial and convergent validity, while its discriminant validity remains doubtful. For WA, problems concerning factorial validity occur.

Despite limited generalizability, the authors provide a first guideline for scholars regarding the empirical validity of BSA and WA outside the context of developed economies.

The current study sheds light on the validity of two PSC-measurement approaches in an emerging economy context. This way, the authors contribute to the field by addressing the scarcity of empirical research and the restricted scope of developed economies regarding PSC-measurement.

The study is aimed at analyzing the perceptions of students and teachers regarding the effectiveness of massive open online courses (MOOCs) on learning efficiency of students and also evaluating MOOCs as an ideal tool for designing a blended model for education.

The analysis was carried out by using the data gathered from the students as well as teachers of University of Mysore, Karnataka, India. Two separate sets of questionnaires were developed for both the categories of respondents. Also, the respondents were required to have prior experience in MOOCs. Further, the collected data was analyzed using statistical package for social sciences (SPSS).

The study showed that MOOCs have a more positive influence on learning efficiency, as opined by both teachers and students. Negative views such as cheating during the assessment, lack of individual attention to students and low teacher-student ratio were also observed.

Many educational institutions view that the MOOCs do not influence learning efficiency and also do not support in achieving their vision. However, this study provides evidence that MOOCs are positively influencing the learning efficiency and also can be employed in a blended model of education so as to promote collaborative learning.

Technology is playing a pivotal role in all fields of life and the education sector is not an exception. It can be rightly said that the technology-based education models such as MOOCs are the need of the hour. This study may help higher education institutions to adopt MOOCs as part of their blended model of education, and, if already adopted, the outcome of the present study will help them to improve the effectiveness of the MOOCs they are offering.

There is an ongoing challenge to map the efficacy of e-retailing strategies in building both value co-creation opportunities for online customers and customer value for companies. Based on the service-dominant (S-D) logic, an integrative model is provided that connects the impact of convenience and personalisation strategies (CPSs) on an e-retailer's performance – by offering co-creation opportunities and customer engagement.

The survey instrument is validated and the model is tested with data from active online customers using a novel methodology that blends artificial neural network (ANN) analysis with partial least squares (PLS) in both the measurement model and the path analysis.

The findings robustly support the model and yield evidence of the contribution of CPSs in effective value propositions, the interface between the S-D logic and customer engagement, and the direct effect of customer engagement on tangible forms of value for companies.

This study is the first scholarly effort to provide a comprehensive understanding of how and why CPSs can maximise customer value for the e-retailer, while simultaneously testing the customer value/engagement interface with a new blended ANN-PLS method.

This research aims to examine the educational philosophy of teachers in classrooms. Teachers' educational philosophy influences the power balance, course content function, student and teacher roles, responsibility for learning and assessment purposes and processes. The research also analyzes whether gender, qualification, specialization and experience significantly influence classroom educational philosophies.

The study utilized a quantitative research design, utilizing data from 193 teachers working in a public higher education institution in the Sultanate of Oman. The study utilized a survey method to solicit data from the respondents. Besides utilizing descriptive statistics such as mean and standard deviation, the study used analysis of variance (ANOVA) and t-test to test the hypotheses.

Analysis revealed an instructional strategy's preference, including elements of both teacher-centered and student-centered educational philosophies. Elements of progressivism, constructivism, reconstructivism and perennialism are more relevant in the teacher's instructional design. The results show no significant differences in teachers' pedagogical philosophy that exist based on gender, specialization and experience. However, teachers' age significantly influences their educational philosophy preferences.

This research centers on a public higher education institution in the Sultanate of Oman, with a particular focus on the Department of Business Studies. This resarch delimits its discussion on teachers' chosen educational philosophy. Other possible factors may also impact student retention and effective teaching and learning.

This research offers valuable insights to academicians, higher education administrators, and policymakers. Specifically, this research emphasizes the significance of employing a blended approach, which incorporates both student-centered and teacher-centered educational philosophies, to enhance student engagement, retention, and effective teaching and learning.

This research emphasizes the importance of educators' adoption of a blended educational philosophy in promoting student retention and engagement within higher education institutions. To achieve desirable outcomes, policymakers in higher education must ascertain which educational philosophy is most effective in the classroom. Additionally, ensuring congruence between preferred educational philosophy and teachers’  instructional practices is vital in facilitating effective teaching and learning.

To the best of the authors’ knowledge, this study is the first of its kind among teachers in higher education in the Sultanate of Oman. The outcome of this study helps detail the specific strategies teachers deploy and categorize into various educational philosophies.

Student attritions in tertiary educational institutes may play a significant role to achieve core values leading towards strategic mission and financial well-being. Analysis of data generated from student interaction with learning management systems (LMSs) in blended learning (BL) environments may assist with the identification of students at risk of failing, but to what extent this may be possible is unknown. However, existing studies are limited to address the issues at a significant scale.

This study develops a new approach harnessing applications of machine learning (ML) models on a dataset, that is publicly available, relevant to student attrition to identify potential students at risk. The dataset consists of the data generated by the interaction of students with LMS for their BL environment.

Identifying students at risk through an innovative approach will promote timely intervention in the learning process, such as for improving student academic progress. To evaluate the performance of the proposed approach, the accuracy is compared with other representational ML methods.

The best ML algorithm random forest with 85% is selected to support educators in implementing various pedagogical practices to improve students’ learning.

This paper aims to identify and evaluate resolutions to key learning and teaching challenges in very large courses that involve practical mathematics, such as foundational finance.

A design-based research approach is used across three semesters to iteratively identify practical problems within the course and then develop and evaluate resolutions to these problems. Data are collected from both students and teachers and analysed using a mixed-method approach.

The results indicate that key learning and teaching challenges in large foundational finance courses can be mitigated through appropriate consistency of learning materials; check-your-understanding interactive online content targeting foundational concepts in the early weeks; connection points between students and the coordinator to increase teacher presence; a sustained focus on supporting student achievement within assessments; and signposting relevance of content for the broader program and professional settings. Multiple design iterations using a co-design approach were beneficial to incrementally improve the course and consider multiple perspectives within the design process.

This paper develops a set of design principles to provide guidance to other practitioners who seek to improve their own courses.

The use of design-based research and mixed-method approaches that consider both student and teacher perspectives to examine the design of very large, foundational finance courses is novel.

Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

The objective of the study was to explore which COVID-19 teaching and learning methods, that enhanced accounting students' learning experience, should be applied at a residential university after the pandemic.

A qualitative exploratory approach within an interpretive paradigm was applied. A total of 15 semi-structured interviews were conducted with accounting students and the data were analysed using thematic analysis.

This study shows how pre-COVID-19 accounting education can be adapted by learning from the teaching and learning experiences gained during the pandemic and that there are various teaching and learning methods that can be applied in the post-COVID-19 period to enhance students' learning experience. These blended active teaching and learning methods include: the flipped classroom, discussion forum, electronic platform (to ask questions during class), key-concept videos and summary videos. Introducing these teaching and learning methods comes with challenges and the study provides recommendations on how to overcome foreseen obstacles. The contribution of the research is that it informs accounting lecturers' decision-making regarding which teaching and learning methods to apply in the aftermath of COVID-19 to enhance students' learning experience.

It is uncertain which teaching and learning methods employed during the COVID-19 pandemic should be applied at a residential university to enhance the teaching and learning experience after the pandemic. Accounting lecturers might return to their pre-COVID-19 modus operandi, and the valuable experience gained during the pandemic will have served no purpose.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.