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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.

Climate change has been identified as a pressing social, environmental and economical challenge that has been unequivocally linked to human activity through latest Intergovernmental Panel on Climate Change (IPCC) reports. It is here to stay with us for generations to come and is already causing severe tribulations across the world. As nations devise policies to mitigate to climate change to stay within the 1.5 degrees Celsius target and small island developing states (SIDS) like Mauritius and the developing world in general find means to adapt to its consequences, a core shortcoming highlighted is the lack of community engagement and grassroots action so that policies permeate to concrete action. Of prime importance for this to happen is raising awareness on the climate change phenomenon, which has so far been a topic deemed complex for the general public, hence creating systemic barriers for climate action. The use of artificial intelligence (AI) can play a significant role in designing such community outreach programmes based on outcomes reported in literature in the educational sector in support of Sustainable Development Goal (SDG) 4: Quality Education. There is growing interest for a green lifestyle in the world population, and this chapter shows how the home can be used as a basic building block for allowing each household to contribute to climate action, while offering an effective case study to raise awareness on climate change through practical examples and demonstration, in support for SDG 11: Sustainable Cities and Communities. Based on an energy-water-materials nexus, the circular home concept is a clear contribution to SDG 13: Climate Action, with huge potential to use AI techniques and underpinning technologies to implement and optimise the efficacy of the proposed measures.

The study attempts to estimate farm subsidies the governments can save by transitioning to a millet-based production system, replacing GHG emission-intensive crops.

It updates a 131 × 131 commodity input–output (IO) table of the year 2015–16 into 2021–22 using the RAS procedure and simulates the economy-wide impacts of replacing rice and wheat with pearl millet and sorghum using consumption and production approaches. It then quantifies fertilizer, electricity and credit subsidy expenses the government can save through this intervention. It also estimates the potential reduction in GHG emissions that the transition could bring about. India is taken as a case.

Results show pearl millet expansion brings greater benefits to the government. It is estimated that when households return to their pearl millet consumption rates that prevailed in the early-reform period, this could save the Indian government Rs. 622 crores (USD 75 m). The savings shall be reinvested in agriculture to finance climate adaptation/mitigation efforts, contributing to a sustainable food system. Net GHG emissions also decline by 3.3–3.6 MMT CO2e.

Indian government has been actively aiming to bring down paddy areas since 2013–14 through the Crop Diversification Program and promoting millets (and pulses and oilseeds) on these farms. The prime reason is to check rapidly declining groundwater irrigation in Green Revolution states. Regulations in the past in these states have not brought the intended results. Meanwhile, electricity and fertilizers are heavily subsidized for agriculture. A slight shift in the cropping system can help conserve these resources. Meanwhile, GHG emissions could also be brought down and subsidies could well be saved. The results of the study indicate the same.

A less warm society is what governments and nongovernment organizations across the world are aiming for at present. Financial implications affect actions against climate change to a greater extent, apart from technological innovations. The effects of policy strategies discussed in the study, taking a large country as a case, when implemented appropriately around the regions, could help move a step closer to action against climate change.

The paper addresses a key but rarely explored research issue – that how a climate-sensitive crop choice will help reduce the government’s fiscal burden to finance climate adaption/mitigation. It also offers a mechanism to estimate the benefits within an economy-wide framework.

The global organic market is expanding, and India is in an advantageous position with the highest number of organic producers worldwide. Although many articles have been published on the value chain of organic products from India, no significant studies were found related to the value chain analysis of organic pineapple. This study aims to know the various aspects of the organic pineapple value chain, i.e. network structure, value addition at various stages of chain actors, value chain upgradation and governance structure.

The study is explorative in nature, and primary data from various actors involved in the chain is collected and analyzed. Primary data through a structured schedule and interviews are collected from farmers and traders. A multistage sampling plan has been adopted. A sample of 75 farmers was randomly selected from the study area. For traders, snowball sampling is used due to the nonavailability of the sampling frame. A total of 10 commission agents, 10 wholesalers and 20 retailers were thus selected for the study. For objectives 1 and 4, descriptive statistics are used. For objective 2, a modified formula described by (Murthy et al., 2007) is used to calculate farmer’s net price and marketing margin. For objective 3, Garrett’s ranking technique is used to identify various constraints in upgrading the organic pineapple value chain in Assam.

This study shows that the value chain of organic pineapple is in the initial stage and proper value addition is required to have a complete regulated value chain. Six marketing channel is identified, and products are sold through farmer producer company only in case of export and trade with distant buyers. The marketing efficiency for channels II and III is 1.69 and 0.99, respectively. The degree of value addition for channel II in the hands of the commission agent, wholesaler and retailer is 11.65%, 4.56% and 12.60%, respectively. In the various constraints in upgrading the value chain, farmers rank “policy support” as a major constraint. In the governance structure, trade with distant traders and exports is done formally and through written contracts.

The study performs value chain analysis of organic pineapple in Cachar district of Assam, India for the year January 2022–January 2023. Future studies are encouraged related to various aspects of the supply chain and value chain of organic pineapple from various northeastern states of India and other states.

The study will help policymakers and key actors to know the existing chain and frame a well-coordinated and regulated value chain.

This study is one of the first study to explore the value chain of organic pineapple of Cachar district of Assam, India. Implementation of these findings can help various actors to strengthen the existing value chain.

In 2015, NESTLÉ India underwent a major crisis as the product which contributed to nearly 30% of its sales had to be taken off the shelves. Maggi—the go-to convenience food for all generations (especially kids and young adults)—which had entered the market in 1983, was banned. With a market share of 70-80% before the ban, NESTLÉ, which got the ban lifted in November 2015, had to undergo the task of winning back the lost market. Over a period of 8 months after its relaunch, the brand regained about 60% of its market back, but the question is how could such brand disaster be avoided in future? The case revolves around a major brand recovering from a brand disaster, and whether they did it well enough or could the situation have been managed better. It also enquires as to what road should be taken forward from here. It notes the action taken by the government against the brand and leaves it to the judgment of the readers if the actions taken against the brand were a little too harsh, solely because MNCs are usually considered a soft target in India. The readers must also understand and analyse the different brand relaunch strategies that were adopted by NESTLÉ and the next steps that should be taken by it.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

Organizational theorists and strategy scholars are both interested in how organizations deal with ambiguity, especially in relation to implementation. This chapter examines one source of ambiguity that organizations face, which is based on their efforts to implement moral mandates. These mandates, which are related to areas such as environmental sustainability and diversity, are inherently ambiguous, as they lack a shared understanding regarding their scope and associated practices. They are also often broad and systemic and may be unclearly aligned with an organization's strategy. Due to these challenges, in this chapter, we theorize that collective action at the field level is necessary for organizations to advance and concretize moral mandates. We examine this theorizing through the case of the implementation of sustainability in higher education. We hypothesize and find support for the idea that when an organization's members engage in collective action at the field level, those organizations have an increased likelihood of achieving sustainability implementation. To gain insight into this field-to-organization relationship, we qualitatively examine 18 years of conversations from an online forum to develop a process model of moral mandate implementation. We theorize that collective action functions as a field-configuring space, in which actors from a variety of organizations come together to (1) refine the scope of the mandate and (2) create an implementation repertoire that actors can draw on when seeking to bring sustainability to their own organizations. Overall, our study provides a model of how ambiguous moral mandates can be implemented by highlighting the important role of collective action across organizations in concretizing those mandates and providing actors with the tools for their implementation.

Amidst unpredictable and turbulent periods, such as the COVID-19 pandemic, service organization’s responses are required to be innovative, adaptable and resilient. The purpose of this study is to explore the utilization of both reconfiguration and transformational strategies as instruments for cultivating resilience and advancing sustainability in service organizations.

The study examines a proposed resilience model using fuzzy logic. The research also used a semantic differential scale to capture nuanced and intricate attitudes. Finally, to augment the validity of the resilience model, a measurement scale was formulated using business mathematics and expert opinions.

Although investing in resilience training can help organizations gain control and maintain their operations in times of crisis, it may not directly help service organizations understand the external turmoil, seek available resources or create adaptive remedies. Conversely, high levels of reconfiguration and transformation management vigour empower a service organization’s revolutionary, malleable vision, organizational structure and decision-making processes, welcoming talented and innovative employees to enhance capabilities during crises.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations identifying the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research guides service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. The study elaborates on the enhancement of resilience, increasing innovation, improving efficiency and enhancing customer satisfaction for service organizations to remain competitive and contribute to positive social and economic outcomes through the adoption of both reconfiguration and transformational strategies.

The study also guides the service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. Rapid innovation and business model innovation are essential components, enabling service organizations to foster a culture of innovation and remain competitive. In addition, the adoption can lead to improved financial performance, job creation and economic growth, contributing to positive social and economic impacts.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations. It identifies the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research also provides a foundation for further investigation into the effectiveness of these strategies and their impact on organizational performance and sustainability. By better preparing service organizations for disruptions and uncertainties, this research triggers ameliorated organizational performance and sustainability.

Within the realm of the service industry, the present investigation has undertaken the development, quantification and scrutiny of both resilience and tenacity. In addition, it has delved into the intricate dynamics surrounding the influencing factors and antecedents that bear upon resilience, elucidating their consequential impact on the operational performance and outlook of service-oriented organizations. The findings derived from this research furnish valuable insights germane to enhancing operational efficacy and surmounting impediments within the sector.