Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence, the adoption of Blockchain is becoming an increasingly significant topic. The number of publications discussing the potential of Blockchain adoption has been expanding significantly. In addition, not enough attention has been given to Blockchain adoption in the software development industry. As a result, a systematic overview to investigate the research trends in this area is needed. This study uses a Scientometric analysis and critical review to examine the evolution of Blockchain adoption research on the Web of Science Principal Collection. In addition, a systematic literature review (SLR) was conducted to identify gaps in Blockchain adoption research and the top reasons for adopting Blockchain with the intention of proposing a sustainable adoption framework. This study extends the body of knowledge by discussing the most influential countries, authors, organizations, publication themes, and most cited publications on Blockchain adoption research. Additionally, this study identifies the 30 relevant studies from the Web of Science and Scopus, including their industries, countries, methods, and respondent sample size, and the top 18 adoption factors among them. Consequently, this study proposes a suitable Blockchain adoption framework based on these top 18 factors. Finally, this study’s aim and unique contribution is to serve as an initial launching point for upcoming Blockchain adoption in software development industry research.

Emotions are vital for identifying an individual’s attitude and mental condition. Detecting and classifying emotions in Natural Language Processing applications can improve Human–Computer Interaction systems, leading to effective decision making in organizations. Several studies on emotion classification have employed word embedding as a feature extraction method, but they do not consider the sentiment polarity of words. Moreover, relying exclusively on deep learning models to extract linguistic features may result in misclassifications due to the small training dataset. In this paper, we present a hybrid feature extraction model using human-engineered features combined with deep learning based features for emotion classification in English text. The proposed model uses data augmentation, captures contextual information, integrates knowledge from lexical resources, and employs deep learning models, including Bidirectional Long Short-Term Memory (Bi-LSTM) and Bidirectional Encoder Representation and Transformer (BERT), to address the issues mentioned above. The proposed model with hybrid features attained the highest Jaccard accuracy on two of the benchmark datasets, with 68.40% on SemEval-2018 and 53.45% on the GoEmotions dataset. The results show the significance of the proposed technique, and we can conclude that the incorporation of the hybrid features improves the performance of the baseline models.

The technology of Blockchain may open up new potential for innovation and distinction. It can enable the software sector to develop more safe and transparent systems that can function in an environment without trust. The adoption rate still needs to be higher despite the potential advantages; the relatively low adoption rate may be attributable to issues such as a lack of awareness, the difficulty of adoption, and ambiguity surrounding legal and regulatory frameworks. Considering technical, organizational, and environmental aspects, this study aims to determine the primary factors impacting the readiness of software firms to adopt Blockchain technology. The research on adopting Blockchain technology in the Malaysian software sector is limited. Using a quantitative method, the researchers used structural equation modeling to analyze 251 survey responses from the Malaysian software sector. In light of the findings, eight hypotheses were considered significant, and one hypothesis was rejected. At the same time, the R² indicated that all these variables explained 71% of the dependent variable’s variance, which is considered substantial. Overall, it makes it easier for firms in the software sector to use Blockchain technology, which would increase the overall competitiveness of Malaysia’s software sector in the international market.

The use of Blockchain is becoming a matter of increasing importance, yet the software development industry has not given Blockchain adoption enough consideration. As a result of their inability to modify their software process within the project life cycle, many software development companies struggle to [adopt Blockchain technology. This is because Blockchain Oriented Software (BOS) and its projects have distinctive characteristics that are distinct from traditional software and projects. The constructs and their items to adopt Blockchain in Software development industry have not been identified or investigated. This study aimed to identify technological, organizational, and environmental constructs and their items to adopt Blockchain. Utilizing a quantitative validation approach, 10 interviews and 25 assessment questionnaires were analyzed. The results reveal the identified technological, organizational, and environmental constructs and their items to adopt Blockchain. Experts unanimously agreed with Content Validity Ratio (CVR) results. According to most evaluation questionnaire forms and interview transcripts, the top technological construct was “Trialability” and the top organizational construct was “Cost” while the top environmental construct was “Market Dynamics.” All other constructs and their items were applicable, as indicated by most evaluation questionnaire forms and interview transcripts. This research gives a comprehensive list of technological, organizational, and environmental constructs and their items that demand the attention of Blockchain adoption researchers and industry players in the software development sector.

Background/Objectives: Delivering high quality software is a big challenge for software companies specifically for SMEs but it is significant asset. This research objective is to evaluate the readiness of Malaysian SME to adopt CMMI with consideration of agile methods and principles. Methods/Statistical Analysis: A survey was conducted with random 40 respondents of the company’s employees like developers, quality engineers and managers and it was a cross sectional survey because the data was gathered in a period of time in order to achieve the objectives. The data was analyzed using statistical analysis technics like bar graph and pie chart. Findings: Based on the survey results, the company is not ready to adopt CMMI officially because the results show that most of the employees agreed on the need to adopt more agile methods and to exercise more agile principles in the company. additionally, the results show that some CMMI practices like establish estimates of work product, task attribute, and plan for project resources were used effectively. On the hand, some essential CMMI practices like identifying configuration items, establishing a configuration management system, and creating baselines were not used sufficiently besides some other CMMI practices like controlling configuration items, tracking change requests, and controlling configuration items were exercised very badly. Application/Improvements: In interests of enhancing the succeed of SPI initiatives based on CMMI for any SMEs, this study suggests SMEs to check their readiness first.