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The objective of this study is to explore the level of understanding and actions taken by the people of Gurugram (erstwhile Gurgaon) to mitigate the impact of climate change, given its critical importance as a global issue.

Using a qualitative approach, primary data were collected through in-depth interviews by means of semi-structured interview methods.

The findings indicate that while people are aware of climate change, the information is deficient for them to translate their knowledge into effective action. Some of the major challenges identified are lack of appropriate understanding, resources, education, motivation and government initiatives, as well as the old habits, peer influence, feeling of incapability and limited media exposure. To bridge the intention-action gap, it is recommended that people should be empowered to act desirably. There is a change need for awareness and education on ways to mitigate the effects of climate change. The study has implications for researchers, environmentalists, policymakers, non-government organizations and local residents of Gurugram.

This study provides unique insights into the understanding of climate change by the general public and challenges faced in taking pro-environment actions. It emphasizes the urgent need to create awareness and educate individuals about ways to mitigate the impact of climate change.

The purpose of this paper is to offer an accessible and interdisciplinary research strategy in organisational ethnography, called action ethnography, that acknowledges key concepts from action research and engaged and immersive ethnography. It aims to encourage methodological innovation and an impact turn in ethnographic practice.

A working definition of “action ethnography” is provided first. Then, to illustrate how an action ethnography can be designed by considering impact from the outset, the author draws on a study she is undertaking with a grassroots human rights monitoring group, based in England, and then discusses advantages and limitations to the approach.

The author suggests three main tenets to action ethnography that embrace synergies between action research and ethnography: researcher immersion, intervention leading to change and knowledge contributions that are useful to both practitioners and researchers.

This paper provides researchers who align with aspects of both action research and ethnography with an accessible research strategy to employ, and a better understanding of the interplay between the two approaches when justifying their research designs. It also offers an example of designing an action ethnography in practice.

Whereas “traditional” ethnography has emphasised a contribution to theoretical knowledge, less attention has been on a contribution to practice and to those who ethnographers engage with in the field. Action ethnography challenges researchers to consider the impact of their research from the outset during the research design, rather upon reflection after a study is completed.

This study aims to investigate how companies’ understanding of the business network influences the creation of value in business-to-business relationships. The authors do this by analysing dimensions in actors’ “network pictures” and illustrating how value perception and network understanding influence actors’ mutual effort to create value. Approaching relationship value from the point of actors’ cognitive understanding of their business network has so far been largely overlooked in relationship value research.

This study applies a qualitative case study methodology whereby dyadic data from a well-established business-to-business relationship is collected from 18 company representatives through personal interviews and group interviews supplemented by participant observations and company data.

The findings contribute with new insight into how companies’ understanding of their surrounding network influence (facilitates or limits) relationship value creation. The authors find that companies continuously reflect on changes in their networks and the related changes in partners’ value perceptions. Through value articulations, companies seek to explicitly express their value perception. Value reflections and value articulations create a dynamic process formed not only by the individual actor but also through their relationship and engagement in their network environment. This requires companies to develop their networking capabilities.

This paper presents findings, insights and contributions limited to a case study of a particular business relationship within an industrial setting. Although the findings and contributions are valid and in line with the criteria for rigorous qualitative research, the authors advocate and call for additional studies that investigate relationships value creation and address the interplay between actors’ network understanding and their actions and behaviour. One way to approach this would be to test the four propositions derived and presented as part of the present study.

The findings imply that management needs to be aware not only of the value created and delivered to a specific partner but also of how the partner’s understanding of the wider network will influence the value delivering and capturing process.

This study contributes to the growing literature on relationship value creation by outlining a dynamic process where relationship partners reflect upon and articulate value. Such activities are influenced by the partners’ network understanding and form the basis of the mutual relationship value creation effort. The findings also contribute to the network pictures literature by emphasizing insights into the formation of value perceptions through actors’ understanding of their surrounding networks.

Growth optimism, which describes the expected future growth of a firm, is an important but underexplored construct in strategy. This paper aims to assess the planning antecedents of such growth optimism by using a large Australian sample of small enterprises.

The authors use a secondary data set, gathered among Australian small to medium enterprises (SMEs), by the Australian Bureau of Statistics (ABS). The analysis adopts a regression approach including a mediated and a non-mediated path to explore the direct and indirect effects of strategic planning and budgetary planning and management on expected future revenues.

This paper assesses the implications of concurrent strategic planning and financial management dynamic capabilities on anticipated future revenue growth, an important predisposition dynamic capability. The authors note that this configuration of actions and predisposition aligns closely with the necessary requirements for growth. The findings suggest that firms that use strategic planning and robust budget planning and monitoring processes exhibit higher optimism about future sales growth and firms that effectively configure these planning activities with market development tend to exhibit higher growth and more growth optimism.

In terms of theoretical contributions, the paper strongly supports the formality view in the formal/informal debates associated with effectuation strategies. The authors suggest that appropriate strategic and budgetary planning and control systems act as a counterbalance to organisational confusion and managerial capriciousness, leading to improved confidence among managers and their employees regarding future resource commitments and plans.

The findings of the paper are potentially important for both managers and policy makers. For managers seeking to grow their future sales, planning is shown to be an important antecedent activity. The presence of financial and strategic planning may predispose firms to make important investment decisions that drive future growth. Also, a better understanding of the firm’s current and future strategic and financial position may be evidence of effective firm management, a situation that, in turn, drives growth.

In terms of social and policy implications, the data gathered for the survey by the ABS forms a valuable collection of information in relation to business practices. Australian firms are required by law to regularly report budget plans and outcomes. The research suggests that this data can inform policy initiatives, particularly in relation to programmes that may assist small and young firms to undertake prospective strategic and budgetary planning.

To the best of the authors’ knowledge, this is the first paper to investigate the particular configuration of strategic and financial planning and anticipated sales growth in the SME context.

Based on the transformative learning theory, this paper analyses a French women-only training programme (WOTP) that aims to develop women’s soft skills in their professional contexts. This paper aims to focus on the process of personal transformation, the collective dimensions and the unexpected effects of the transformation.

This paper used a mixed qualitative design that mainly combines a qualitative two-step study of 47 women to assess their personal changes in terms of self-confidence, self-efficacy and assertiveness. This paper used 13 semi-structured interviews to explore the perceived changes in-depth.

The analysis shows that beyond “fixing their lack of skills” – including self-limiting behaviours, low feelings of self-efficacy and difficulty claiming one’s place – a WOTP can trigger a transformational learning experience at the individual level and can modify the surveyed women’s attitudes and behaviours at work. The results also highlight the collective dimension of transformation and, to some extent, an avenue for a societal transformation.

One can state that these WOTPs may positively contribute to human resources development in organisations, and that they may be considered a relevant practice in the move to promote women and gender diversity in organisations.

The findings reveal that, at their individual levels, these women may become agents of change by influencing and acting in their professional lives. The results stress that training women may contribute to organisational changes in terms of gender diversity. These findings contribute to the enrichment of the transformative learning theory by developing the collective and societal dimensions.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

A mixed-method study was performed to determine the impact of integrating systems thinking (ST) into an electronic learning module for junior high school teachers in the Philippines. The study aims to assess how an ST approach to pedagogy compared against a conventional approach in terms of contribution to the participants’ global climate change content knowledge, holistic thinking and depth and accuracy of knowledge and reasoning.

The study implemented e-learning modules using an ST approach versus a conventional approach in teaching climate science to junior high school teachers. The paper presents quantitative data obtained from pre and posttests results of the 20 teacher-participants and qualitative data obtained during the focus-group discussion (FGD) after the implementation of the study.

The results from the statistical analysis indicated that the ST group obtained a significant increase in their assessment scores compared to the non-ST group, according to predetermined criteria. Content knowledge, depth and accuracy of knowledge and reasoning increased the most. The participants mentioned during the FGD that the module helped deepen their understanding of climate change.

The study was limited to 20 teacher-participants, but it has relevance for public school teachers in the country given that participants had raised concerns regarding the lack of training in their schools for teaching climate science. They admitted that they lacked critical information to include in climate change topics in their classes.

This paper shows how the ST approach can be used to teach climate change to junior high students. The e-learning module can provide teachers with better understanding, knowledge and reasoning to teach climate change to high school students more effectively.

The purpose of this study is to determine if blockchain-supported carbon offset information provision and shipping options with different cost and environmental footprint implications impact consumer perceptions toward retailers and logistics service providers. Blockchain and carbon neutrality, each can be expensive to adopt and complex to manage, thus getting the “truth” on decarbonization may require additional costs for consumers.

Experimental modeling is used to address these critical and emergent issues that influence practices across a set of supply chain actors. Three hypotheses relating to the relationship between blockchain-supported carbon offset information and consumer perceptions and intentions associated with the product and supply chain actors are investigated.

The results show that consumer confidence increases when supply chain carbon offset information has greater reliability, transparency and traceability as supported by blockchain technology. The authors also find that consumers who are provided visibility into various shipping options and the product's journey carbon emissions and offset – from a blockchain-supported system – they are more willing to pay a premium for both the product and shipping options. Blockchain-supported decarbonization information disclosure in the supply chain can lead to organizational legitimacy and financial gains in return.

Understanding consumer action and sustainable consumption is critical for organizations seeking carbon neutrality. Currently, the literature on this understanding from a consumer information provision is not well understood, especially with respect to blockchain-supported information transparency, visibility and reliability. Much of the blockchain literature focuses on the upstream. This study focuses more on consumer-level and downstream supply chain blockchain implications for organizations. The study provides a practical roadmap for considering levels of blockchain information activity and consumer interaction.

Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

In developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.

The authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.

The authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.

This research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.