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Researchers and policymakers are figuring out the adaptation technologies to cope with the changing climate. Adaptation strategies for crop production followed by the farmers at selected study locations had ranged from 6-30 per cent only, and this was mainly due to lack of awareness about the actual cost associated with adaptation and non-adaptation of these strategies.

Hence, this study aims to address the cost of adaptation for rice using joint probability distribution of rainfall and crop prices.

Cost of adaptation varied from INR2,389 to 4,395/ha for System of Rice Intensification (SRI); INR646 to 1,121/ha for alternate wetting and drying (AWD) and INR8,144 to 8,677/ha for well irrigation (WI), whereas expected cost for not using these technologies has ranged from INR6,976 to 9,172/ha for SRI; INR4,123 7,764/ha for AWD and INR10,825 to 17,270/ha for WI. Hence, promotion of the adaptation technologies itself will minimize the income losses to the farmers.

Even though, there are many ways for farmers (other than technology), to adapt to climate change (such as out-migration to cities, selling farm assets, focus on children’s education, etc.), this report, given the framework of the major research study undertaken, addresses only farm-level adaptation of the technologies to enhance farm income.

Public–private partnership in providing the technologies at cheaper costs, capacity building in handling the technologies and creating awareness about the technologies to minimize the expected cost of adaptation are suggested to improve the adoption level.

The world is increasingly threatened by climate change. As the dimensions of this danger grow, it becomes essential to develop the most effective policies to mitigate its impacts and adapt to these new conditions. Technology is one of the most crucial components of this process, and this study focuses on examining climate change adaptation technologies. The aim of the study is to investigate the entire spectrum of technology actors and to concentrate on the technology citation network established from the past to the present, aiming to identify the core actors within this structure and provide a more comprehensive outlook.

The study explores patent citation relationships using social network analysis. It utilizes patent data published between 2000 and 2023 and registered by the US Patent and Trademark Office.

Study findings reveal that technologies related to greenhouse technologies in agriculture, technologies for combatting vector-borne diseases in the health sector, rainwater harvesting technologies for water management, and urban green infrastructure technologies for infrastructure systems emerge as the most suitable technologies for adaptation. For instance, greenhouse technologies hold significant potential for sustainable agricultural production and coping with the adverse effects of climate change. Additionally, ICTs establish intensive connections with nearly all other technologies, thus supporting our efforts in climate change adaptation. These technologies facilitate data collection, analysis, and management, contributing to a better understanding of the impacts of climate change.

Existing patent analysis methods often fall short in detailing the unique contributions of each technology within a technological network. This study addresses this deficiency by comprehensively examining and evaluating each technology within the network, thereby enabling us to better understand how these technologies interact with each other and contribute to the overall technological landscape.

The purpose of this study is to reveal both the adaptations of information computer technology (ICT) teachers teaching the information technologies and software (ITS) course online during the pandemic and the factors that affect this adaptation process. Teachers’ endeavours to conduct their courses online, the support they take during their endeavours, and their relationships with such basic components as the environment, content and students during this adaptation process will be revealed within the framework of unified theory of acceptance and use of technology (UTAUT).

In this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed. The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study. In this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed ( Creswell, 2009). The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study.

The ICT teachers’ adaptations to the online courses have developed positively over the sub-dimensions of UTAUT, which are performance expectancy (PE), effort expectancy (EE), social influence (SE), facilitating conditions (FC) and behavioural intention (BI). The ICT teachers’ adaptations to the online instruction process have a significant effect on PE, FC and BI on the basis of gender, and on PE and EE on the basis of course content quality. In the process whereby the ICT teachers carry out the ITS course online, the sub-dimensions of PE, SE and FC are significantly predictive of the BI.

UTAUT has been taken as a guiding framework in explaining and discussing the adaptations. Similarly, in other studies focussing on adaptation, this model could be employed in planning the research process. In addition, this study has followed a method in which qualitative data are mostly used to explain the quantitative data. Further studies may adopt a process whereby qualitative data are largely used to describe the way ITS course is conducted in online environments and this process may be used to develop a model.

Examining the students’ BIs in online courses overlaps with the sub-dimension of PE in this study, which stresses that PE, EE and motivation are significantly and directly effective on the students’ intentions of using the online courses, while there is a difference between these two studies in terms of the dimension of EE. The factors such learning outcome, curriculum, attendance to the course, use of materials and tools, interaction and technological substructure appear to be affected by this dimension, so they could be taken as important in that they reveal the importance of the study.

This study may provide clues for the online instruction practices that it reveals teachers’ adaptations to online learning environments at secondary schools. On the other hand, software, hardware, coding and robotics take place in the subjects like product designing, developing and programming that are within the content of ITS course for secondary schools. Even though there is a curriculum prepared for these subjects, a lot of different instruction techniques can be used for the teaching of these subjects. This can allow some inferences about the environments and methods suitable for the online instruction of the related subjects.

This paper aims to examine how high involvement HRM (HIHRM), technology adaptation and innovativeness influence employees to respond to technology innovation performance – that is, radical innovation performance and incremental innovation performance – in distinct ways.

The purposive judgmental sample technique is used to assess the perceptions of 545 IT employees in Bangladesh's ready-made garment (RMG) industry. The partial least square-structural equation modeling (SEM-PLS) method is applied to analyze and interpret the data.

Findings of the analysis show that HIHRM, technology adaptation and innovativeness influence employees to exhibit technology innovation performance. Furthermore, both technology adaptation and innovativeness show the significant mediating effects between HIHRM and technology innovation performance.

First, this study’s findings contribute to HIHRM and technology innovation performance within the context of the resource-based theory. Second, the RMG organizations would acknowledge the role of HIHRM on employee technology adaptability and innovation capability in this regard. A future study might point to the models' ability to create the best work environments, which can help organizations to boost employee productivity through adaptation and innovation.

The study would offer a distinctive perspective on higher-order HIHRM and how they affect IT employees in RMG organizations in Bangladesh that could be approached in other labor-intensive and developing nations. This study also expands the research on technology adaptation and innovativeness by exploring the mediating roles between HIHRM and employee technology innovation performance in the organization.

The purpose of this study is to evaluate to what extent the Paris Agreement and the United Nations Framework Convention on Climate Change (UNFCCC) have supported (or could support) the least developed countries (LDCs) particularly for accessing the climate technologies and thereby to meet the objectives of the Paris Agreement.

This study adopted legal dogmatism to evaluate the gradual development of technology transfer issues to support the LDCs under the international climate regime.

This study suggested a few potential measures to facilitate meaningful technology transfer to LDCs – such as clarifying and linking the role of the technology and financial mechanism, a more robust role of capacity building, using the sustainable development mechanism with a technology transfer focus, improving the transparency and reporting mechanism to particularly indicate support regarding technology transfer requested and received by the LDCs linking it with the nationally determined contributions, and adapting a pragmatic approach to intellectual property.

This study is an original contribution as it identified concern over technology transfer under the UNFCCC since 1992 with a focus on the LDCs and indicated required actions that need to be taken to support the LDCs in the context of climate-related technology transfer and beyond.

Technological process innovation (TPI) is a distinctive organizational phenomenon characterized by a firm-internal locus and underlying components such as mutual adaptation of new technology and existing organization, technological change, organizational change, and systemic impact. The purpose of this paper is to investigate the management of these components at different stages of the innovation lifecycle (ILC) in large manufacturing companies.

The authors adopt an exploratory case-based research design and conduct a multiple case study of five large successful manufacturing companies operating in different industries in Germany. The authors build the study on 55 semi-structured interviews, which yielded 91.5 hours of recorded interview data. The authors apply cross-case synthesis and replication logic to identify patterns of how companies address process innovation components at different ILC stages.

The study uncovers the content of four central TPI components across the ILC and identifies differences between the development of core and non-core processes. Based on the findings the authors describe asymmetric adaptation as a theoretical construct and propose that companies seek different levels of process standardization depending on the type of process they develop, which in turn affects whether there is a greater extent of technological or organizational change.

Awareness of existing structures, processes, and technologies, as well as their value in relation to the company’s core and non-core operations is imperative to determining the adequate structure of mutual adaptation.

The authors provide detailed insight on the management of mutual adaptation, technological, and organizational change, as well as systemic impact at the different stages of the ILC. The authors extend prior research by adopting an ILC perspective for the investigation of these four TPI components and by proposing a construct of asymmetric adaptation to capture key mechanisms of process development and implementation.

This paper aims to propose an approach to examining the long-term impact of the COVID-19 pandemic on business, which presents a unique opportunity to study a hitherto-unavailable business scenario.

A conceptual framework is suggested to study the ability of a service firm to make adaptations to pandemic conditions based on the nature of its services: namely, the act of production and the type of recipient and the predisposed ability of the customer to accept the service firm’s adaptations to social distancing restrictions. Under this framework, it is demonstrated that service adaptations made due to COVID-19 business restrictions and the customers’ acceptance of them determine whether these changes are likely to become permanent.

A classification scheme is developed to determine four classes of service firms’ adaptations to their normal course of business made under pandemic conditions and suggestions given on how to project which adaptations may persist beyond the pandemic and why.

A conceptual framework grounded on Lovelock classification to present projections needs to be empirically tested.

Managerial insights based on the study and suggestions for research on what business practices are most likely to be permanently changed in a post-pandemic world for services are offered.

Using two of Lovelock’s dimensions pertaining to the nature of production and delivery of the service, four categories are proposed based on two characteristics: service adaptability and customer acceptance. The Technology Acceptance Model 2 (TAM2) model is extended to predict service adaptations, which are most likely to become permanent in a post-pandemic world.

Changing climate has increasingly become a challenge for smallholder farmers. Identification of technical, institutional and policy interventions as coping and adaptation strategies and exploring risks of their adoption for smallholder farms are the important areas to consider. The aim of the present study was to carry out an in-depth analysis of adaptation strategies followed and the associated risk premium in technology adoption.

The study was carried out in the dryland systems of three Indian states – Andhra Pradesh, Karnataka and Rajasthan – and was based on a survey of 1,019 households in 2013. The flexible moment-based approach was used for estimating the stochastic production function, which allowed estimation of the relative risk premium that farmers are willing to pay while adopting the technologies to avoid crop production risks.

In all the three states, the risk premium (INR ha⁻¹) was higher for farm mechanization compared to supplemental irrigation, except in the case of Andhra Pradesh. The higher the level of technology adoption, the higher the risk premium that households have to pay. This can be estimated by the higher investment needed to build infrastructure for farm mechanization and supplemental irrigation in the regions. The key determinants of technology adoption in the context of smallholder farmers were climatic shocks, investment in farm infrastructure, location of the farm, farm size, household health status, level of education, married years, expected profit and livestock ownership.

Quantification of the risk premium in technology adoption and conducting associated awareness programs for farmers and decision-makers are important to strengthen evidence-based adoption decisions in the dryland systems of India.

The increasing global competition, worldwide economic and political uncertainities, and continuously changing dynamics in business environment require companies act differently and differentiate via smart strategies in order to have sustainable operations, growth, and profitability. Therefore, firms should be more agile, creative, and adaptive in planning and strategizing their mid- to long-term business objectives.

In that regard, for the last decade globally many firms across all industries seek opportunities to utilize benefits of digitalization. Lately, COVID-19 has also accelerated companies' efforts and investments in digital platforms.

Today, supply chain and procurement functions are expected to have a strategic role for organizations contributing to management decisions. The digital transformation in procurement is promising to enhance and lean the total workflow of operations. Data analytics, artificial intelligence, robotics, and other emerging digital technologies are all highly powerful tools supporting strategic supply and supplier management, providing predictability for demand planning as well as value-based negotiation power to buyers.

On the other hand, there are still challenges and conflicts throughout this transformation process. Level of technological maturity, infrastructure and investment decisions, expertise and competency of procurement professionals, cultural adaptation, and compliance of related stakeholders are some of the key barriers that are addressed with a unique model in this chapter.

Digital era offers a lot of advantages to firms to improve their procurement facilities and practices while it may still take time both for the technologies to fully evolve and also for companies to adapt and embrace digitalization on their benefit.