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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 strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

This study aims to explore the impact of strategic agility on strategic orientation and its dimensions (retrenchment, perseverance, innovation and exit strategies) in Jordanian medical and pharmaceutical industries companies during the COVID-19 crisis.

The researchers relied on a descriptive-analytic methodology. The study population consisted of 23 companies in the medical and pharmaceutical industries in Amman, Jordan. The sampling units were the top managers of these companies, represented by chief executive officers and main department managers. The sample size was 193. Questionnaires were distributed to collect the data, while the valid for analysis were 165 questionnaires.

The results showed that strategic agility has a positive effect on strategic orientation, as well as on, perseverance, and innovation strategies, but it has an opposite effect on retrenchment strategy. However, it has no statistically significant effect on the exit strategy.

This pioneering study is uniquely valuable through filling a gap in the literature by examining the dynamic relationship between strategic agility and strategic orientation, offering practical insights for decision-makers to enhance resilience that contributes to overcoming the COVID-19 and future crises.

This study aims to investigation of the guar gum-manganese dioxide (GG/MnO₂) nanocomposite (NC) synthesized using an environment-friendly method and the degradation of reactive yellow (RY 145) dye in the UV system.

Characterization of the GG/MnO₂ NCs were conducted using field emission scanning electron microscopy, X-ray diffraction and Fourier-transform infrared spectroscopy. Experiments were conducted using a 1 L glass reactor coupled with Ultraviolet (UV-C) blue light bulb of wavelength 250 nm and power of 8 W.

The NC (2.25 g/L) displayed high RY 145 dye degradation (81%) with 10 mg/L of concentration at pH 3. The coefficient of determination (R² 0.99) also depicted that the model fits the experimental data. The analysis of variance (ANOVA) showed that the F-values of 464.75, 276.04 and 5.15 are related to the dose of GG/MnO₂ NCs, initial concentration of RY 145 dye and solution pH, respectively.

The GG/MnO₂ NCs followed by photo oxidation process (UV-process) could be used to degrade the RY 145 dye from synthetic wastewater.

There are two main innovations. One is that the novel process is performed successfully for RY 145 dye degradation. The other is that the optimized conditions are obtained by Box–Behnken design. Also, the effects of different variables on the RY 145 dye removal efficiency were investigated.

The purpose of this paper is to propose an implementation model for enterprise resource planning (ERP) based on resource-based view, and using the dynamic capability theory as its theoretical foundation. This model includes: the establishment of the objectives of the implementation, an assessment of the available resources and the scope of the implementation, the redesign/integration and organizational learning during the process, the implementation of the system, and the measurement and evaluation of its performance.

An integrated circuits design company in Taiwan was used in a case study to examine the validity of the proposed model.

When the proposed ERP implementation model was applied in this study, the results show that organizational coordination, system-process redesign and integration, and organizational learning are the critical strategies for enterprises, in order to reduce the risks during the implementation of ERP projects.

This model can help enterprises recognize the resources needed when implementing an ERP. In addition, they need to consider the reliability of these resources, as this will increase the efficiency of the implementation, and thus the probability of success.

Studies of past models in the implementation of ERP have been conducted in various industries. There is a need for further studies that evaluate the different concepts in terms of the effectiveness of specific methods, in order to enhance the probability of successfully implementing a dynamic system. This paper is one of the first to explain how an enterprise can implement an ERP that is based on the theory of dynamic capabilities. The case study illustrates the important, critical success factors.

This work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies.

In the age of Big Data, all companies want to benefit from large amounts of data. These data can help them understand their internal and external environment and anticipate associated phenomena, as the data turn into knowledge that can be used for prediction later. Thus, this knowledge becomes a great asset in companies' hands. This is precisely the objective of data mining. But with the production of a large amount of data and knowledge at a faster pace, the authors are now talking about Big Data mining. For this reason, the authors’ proposed works mainly aim at solving the problem of volume, veracity, validity and velocity when classifying Big Data using distributed and parallel processing techniques. So, the problem that the authors are raising in this work is how the authors can make machine learning algorithms work in a distributed and parallel way at the same time without losing the accuracy of classification results. To solve this problem, the authors propose a system called Dynamic Distributed and Parallel Machine Learning (DDPML) algorithms. To build it, the authors divided their work into two parts. In the first, the authors propose a distributed architecture that is controlled by Map-Reduce algorithm which in turn depends on random sampling technique. So, the distributed architecture that the authors designed is specially directed to handle big data processing that operates in a coherent and efficient manner with the sampling strategy proposed in this work. This architecture also helps the authors to actually verify the classification results obtained using the representative learning base (RLB). In the second part, the authors have extracted the representative learning base by sampling at two levels using the stratified random sampling method. This sampling method is also applied to extract the shared learning base (SLB) and the partial learning base for the first level (PLBL1) and the partial learning base for the second level (PLBL2). The experimental results show the efficiency of our solution that the authors provided without significant loss of the classification results. Thus, in practical terms, the system DDPML is generally dedicated to big data mining processing, and works effectively in distributed systems with a simple structure, such as client-server networks.

The authors got very satisfactory classification results.

DDPML system is specially designed to smoothly handle big data mining classification.

To develop a fuzzy causal model of enterprise flexibility dimensions in a case study of Indian pharmaceutical industry.

The eight dimensions of enterprise flexibility were identified based on literature review. Fermatean fuzzy decision-making trail and evaluation laboratory (FF-DEMATEL) technique is applied to develop the cause-and-effect interrelationship model among various enterprise flexibility dimensions.

The information technology flexibility, supply chain flexibility, technical flexibility and marketing flexibility are found to be causing/influencing other flexibilities and contributing to overall enterprise flexibilities. Therefore, more attention needs to be paid to develop and sustain them for competitive advantage.

Fermatean fuzzy sets offer more flexibility and more accurate handling complex uncertain group decision making. FF-DEMATEL is a more accurate method to develop inter-dependencies and causal model than ISM, TISM. Ratings from the limited number of decision experts (DEs) from few pharmaceutical firms were done. Future study should take bigger sample of firms and more number of DEs to generalize the findings.

The model will help managers in pharmaceutical industry to prioritize the dimensions of enterprise flexibility to achieve agility, responsiveness, resilience and competitive advantage.

To the best knowledge of the authors, causal modeling enterprise flexibility dimensions using FF-DEMATEL has been studied for the first time in a developing economy context.

These implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.

This paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.

The variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.

The simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.