Requirements elicitation is the process through which analysts determine the software requirements of stakeholders. Requirements elicitation is seldom well done, and an inaccurate or incomplete understanding of user requirements has led to the downfall of many software projects. This paper proposes a classification of problem types that occur in requirements elicitation. The classification has been derived from a literature analysis. Papers reporting on techniques for improving requirements elicitation practice were examined for the problem the technique was designed to address. In each classification the most recent or prominent techniques for ameliorating the problems are presented. The classification allows the requirements engineer to be sensitive to problems as they arise and the educator to structure delivery of requirements elicitation training.

Aim/Purpose: Although cassava is one of the crops that can be grown during the dry season in Northeastern Thailand, most farmers in the region do not know whether the crop can grow in their specific areas because the available agriculture planning guideline provides only a generic list of dry-season crops that can be grown in the whole region. The purpose of this research is to develop a predictive model that can be used to predict suitable areas for growing cassava in Northeastern Thailand during the dry season. Background: This paper develops a decision support system that can be used by farmers to assist them determine if cassava can be successfully grown in their specific areas. Methodology: This study uses satellite imagery and data on land characteristics to develop a machine learning model for predicting suitable areas for growing cassava in Thailand’s Nakhon-Phanom province. Contribution: This research contributes to the body of knowledge by developing a novel model for predicting suitable areas for growing cassava. Findings: This study identified elevation and Ferric Acrisols (Af) soil as the two most important features for predicting the best-suited areas for growing cassava in Nakhon-Phanom province, Thailand. The two-class boosted decision tree algorithm performs best when compared with other algorithms. The model achieved an accuracy of .886, and .746 F1-score. Recommendations for Practitioners: Farmers and agricultural extension agents will use the decision support system developed in this study to identify specific areas that are suitable for growing cassava in Nakhon-Phanom province, Thailand Recommendation for Researchers: To improve the predictive accuracy of the model developed in this study, more land and crop characteristics data should be incorporated during model development. The ground truth data for areas growing cassava should also be collected for a longer period to provide a more accurate sample of the areas that are suitable for cassava growing. Impact on Society: The use of machine learning for the development of new farming systems will enable farmers to produce more food throughout the year to feed the world’s growing population. Future Research: Further studies should be carried out to map other suitable areas for growing dry-season crops and to develop decision support systems for those crops.

Aim/Purpose: This study aims to answer the research question titled What are the competencies required for the Business Process Analyst (BPA) role in organizations with ERP systems in Kenya. Through 4 hypotheses, this study focuses on two specific aspects: (1) Enhancing BPM Maturity and (2) ERP implementation. Background: The emergence of complex systems and complex processes in organizations in Kenya has given rise to the need to understand the BPM domain as well as a need to analyze the new roles within organizational environments that drive BPM initiatives. The most notable role in this domain is the BPA. Furthermore, many organizations in Kenya and across Africa are making significant investments in ERP systems. Organizations, therefore, need to understand the BPA role for ERP systems implementation projects. Methodology: This study uses a sequential mixed methods approach analyzing quantitative survey data followed by the analysis of qualitative interview data. Contribution: The main contribution of this study is a description of competencies that are critical for the BPA in Kenya both in terms of enhancing BPM maturity and for driving ERP systems implementations. In addition, this study sheds light on critical BPA competencies that are perceived to be undervalued in the Kenyan context. Findings: Findings show that business process orchestration competencies are important for driving BPM maturity and for ERP systems implementations. This study found that business process elicitation, business analysis, business process improvement and a holistic overview of business thinking are often overlooked as critical competencies for BPAs but are nevertheless critical for building the BPA practitioner. Recommendations for Practitioners: From this study, practitioners such as top managers and BPAs can be enlightened on the specific competencies that require focus when carrying out BPM and when implementing ERP systems projects. Future Research: The next step is to investigate the interventions that organizations implement to build their BPA competencies. The main aim of this would be to describe those interventions that impact the requisite BPA competencies especially those competencies that were seen to be undervalued within the Kenyan context.

Aim/Purpose: The study describes empirical research into agile Requirements Engineering (RE) practices based on an analysis of data collected in a large higher education organization. Background: Requirements Engineering (RE) in agile development contexts is considerably different than in traditional software development. The field of agile RE is still nascent where there is a need to evaluate its impact in real-world settings. Methodology: Using a case study methodology, the study involved interviewing nine experienced software practitioners who reflected on the use and implementation of various agile RE practices in two software development projects of a student management system. Contribution: The primary contribution of the paper is the evaluation of agile RE practices in a large tertiary educational organization. Based on the analysis of the data, it provides valuable insights into the practice of agile RE in a specific context (i.e., education), but just as importantly, the ones that were omitted or replaced with others and why. Findings: While the evolutionary and iterative approach to defining requirements was followed in general, not all agile practices could be fully adhered to in the case organization. Although face-to-face communication with the customers has been recognized as one the most important agile RE practices, it was one of the most difficult practices to achieve with a large and diverse customer base. Addressing people issues (e.g., resistance to change, thinking, and mindset) was found to be a key driver to following the iterative RE process effectively. Contrary to the value-based approach advocated in the literature, the value-based approach was not strictly adhered to in requirements prioritization. Continuous integration was perceived to be a more beneficial practice than prototyping, as it allows frequent integration of code and facilitates delivering working software when necessary. Recommendations for Practitioners: Our study has important implications for practitioners. Based on our empirical analysis, we provide specific recommendations for effective implementation of agile RE practices. For example, our findings suggest that practitioners could address the challenges associated with limited face-to-face communication challenges by producing flexible, accessible, and electronic documentation to enable communication. Recommendations for Researchers: Researchers can use the identified agile RE practices and their variants to per-form in-depth investigations into agile requirements engineering in other educational contexts. Impact on Society: There are a number of new technologies that offer exciting new opportunities that can be explored to maximize the benefits of agile and other requirements techniques. Future Research: Future research could conduct case studies in different contexts and thus con-tribute to developing bundles or collections of practices to improve software development processes in specific contexts.

Knowledge management and knowledge assets have gained much prominence in recent years and are said to improve organizational performance. Knowledge capture and acquisition mechanisms enhance organizational memory and performance. However, knowledge capture and acquisition mechanisms in higher education institutions are not well known. The aim of this study was to investigate the knowledge capture and acquisition mechanisms at Kisii University. This was a case study in which data were collected through interviews and questionnaires. Purposive sampling was used to determine interview participants while questionnaire respondents were selected through stratified random sampling. Qualitative and quantitative data were analysed using SPSS® student version 14; it revealed that there were various knowledge capture and acquisition mechanisms at Kisii University. It was also established that the University encountered various challenges in knowledge capture and acquisition and lacked some essential knowledge capture and acquisition mechanisms. In this regard, this study proposed knowledge capture and acquisition guidelines that may be adopted by the University to enhance its organizational memory and performance.

Aim/Purpose: This study investigates the issue of knowledge acquisition among faculty members. Background: The paper reports the use of knowledge acquisition tools and reading knowledge sources by faculty members. It also identifies demographic differ-ences among participants in using knowledge acquisition tools and reading knowledge sources. Methodology: The study used an online survey-based questionnaire tool for data collection. The participants consisted of 300 faculty members from 26 academic institu-tions in UAE. Statistical tests are used to verify and validate the hypotheses. Contribution: The paper represents one of the few empirical studies conducted on knowledge acquisition among faculty members in the GCC countries. Find-ings of the study may contribute to the theoretical and practical understanding of knowledge acquisition among faculty members. Findings: Findings of the study revealed that medical faculty members read knowledge acquisition sources more than other faculty members. Likewise, IT faculty members use knowledge acquisition tools more than other faculty members. Results of the study supported stage three of knowledge acquisition proposed in the “Stage Theory of Knowledge Consumption Growth” (Mathew, 1985). The study found that journals are the most sources read by the participants while web-based training (WBT) tools are the most used knowledge acquisition tools among faculty members. Results of the study indicated significant differ-ences among faculty members of different age groups, academic ranks, aca-demic specializations, and institutional affiliation in reading knowledge sources. Likewise, findings of the study revealed significant difference among partici-pants of different academic specializations in using knowledge acquisition tools. Recommendations for Practitioners: Results of the study could be extrapolated to other faculty members in the GCC countries. Recommendation for Researchers: More researches could be done to address different issues of knowledge acquisition among faculty members. Impact on Society: Faculty reading of knowledge sources and use of knowledge acquisition tools may have direct or indirect positive impacts on innovation, creativity, and re-search productivity in any society. Future Research: It will be interesting to apply more than one data collection method in the future research.

Aim/Purpose: This study explores how women-led SMMEs in developing countries, specifically in the Mozambican context, institutionalise e-commerce by focusing on the ongoing interaction between the SMME, its context, and process of e-commerce institutionalization. Background: It is believed that institutionalization of e-commerce provides significant benefits of unlimited access to new markets, and access to new, improved, inexpensive and convenient operational methods of transacting. Although prior studies have examined the adoption of e-commerce and the enabling and constraining factors, few have examined e-commerce (i) institutionalization (that is, post-adoption), and (ii) from a gender perspective. This study aims to respond to this paucity in the literature by exploring how women-led SMMEs in developing countries, specifically in the Mozambican context, institutionalise e-commerce. Methodology: The study follows a qualitative inquiry approach for both data collection and analysis. Semi-structured interviews were adopted for data collection and thematic analysis implemented on the data. SMMEs were purposively sampled to allow for the selection of information-rich SMMEs for study and specifically those that have gone through the experience of adoption and in some cases have institutionalized e-commerce. Contribution: The empirical findings explain how the institutionalization process from interactive e-commerce to transactive e-commerce unfolds in the Mozambican context. Findings: Transition from interactive to transactive e-commerce is firstly influenced by (i) the type of business the SMME is engaged in; and (ii) customer and trading partner’s readiness for e-commerce. Secondly, the transition process is influenced by the internal factors of (i) manager’s demographic factors; (ii) mimetic behaviour arising from exposure to (foreign) organizations in the same industry that have mature forms of e-commerce; (iii) the business networks developed with some of these organizations that have mature forms of e-commerce; (iv) access to financial resources; and (v) social media technologies. Thirdly, the process is influenced by external contextual factors of (i) limited government intervention towards e-commerce endeavors; (ii) limited to lack of financial institutions readiness for e-commerce; (iii) lack of local available IT expertise; (iv) consumer’s low purchasing power due to economic recessions; (vi) international competitive pressure; and (vii) sociocultural practices. Recommendations for Practitioners: The study provides SMME managers, practitioners, and other stakeholders concerned with women’s development with a better understanding of the process in order to develop appropriate policies and interventions that are suitable for the reality of women-led SMMEs in Mozambique and other developing countries with similar contextual characteristics. Recommendation for Researchers: The study contributes to the existing debate of e-commerce and the use of ICT for development in developing countries by providing a distinct contribution of the institutionalization process and how the contextual structures influence this process. Impact on Society: Women-led SMME managers can learn from the different experiences, and compare their e-commerce efforts with SMMEs that were able to institutionalize and make strategies for improvements within their organizations. Future Research: The manner in which women-led SMMEs employ e-commerce requires further investigation to understand how issues related to gender, the cultural context, and different regions or countries impact this process.

Aim/Purpose: Acquisitions play a pivotal role in the growth strategy of a firm. Extensive resources and time are dedicated by a firm toward the identification of prospective acquisition candidates. The Indian manufacturing sector is currently experiencing significant growth, organically and inorganically, through acquisitions. The principal aim of this study is to explore models that can predict acquisitions and compare their performance in the Indian manufacturing sector. Background: Mergers and Acquisitions (M&A) have been integral to a firm’s growth strategy. Over the years, academic research has investigated multiple models for predicting acquisitions. In the context of the Indian manufacturing industry, the research is limited to prediction models. This research paper explores three models, namely Logistic Regression, Decision Tree, and Multilayer Perceptron, to predict acquisitions. Methodology: The methodology includes defining the accounting variables to be used in the model which have been selected based on strong theoretical foundations. The Indian manufacturing industry was selected as the focus, specifically, data for firms listed in the Bombay Stock Exchange (BSE) between 2010 and 2022 from the Prowess database. There were multiple techniques, such as data transformation and data scrubbing, that were used to mitigate bias and enhance the data reliability. The dataset was split into 70% training and 30% test data. The performance of the three models was compared using standard metrics. Contribution: The research contributes to the existing body of knowledge in multiple dimensions. First, a prediction model customized to the Indian manufacturing sector has been developed. Second, there are accounting variables identified specific to the Indian manufacturing sector. Third, the paper contributes to prediction modeling in the Indian manufacturing sector where there is limited research. Findings: The study found significant supporting evidence for four of the proposed hypotheses indicating that accounting variables can be used to predict acquisitions. It has been ascertained that statistically significant variables influence acquisition likelihood: Quick Ratio, Equity Turnover, Pretax Margin, and Total Sales. These variables are intrinsically linked with the theories of liquidity, growth-resource mismatch, profitability, and firm size. Furthermore, comparing performance metrics reveals that the Decision Tree model exhibits the highest accuracy rate of 62.3%, specificity rate of 66.4%, and the lowest false positive ratio of 33.6%. In contrast, the Multilayer Perceptron model exhibits the highest precision rate of 61.4% and recall rate of 64.3%. Recommendations for Practitioners: The study findings can help practitioners build custom prediction models for their firms. The model can be developed as a live reference model, which is continually updated based on a firm’s results. In addition, there is an opportunity for industry practitioners to establish a benchmark score that provides a reference for acquisitions. Recommendation for Researchers: Researchers can expand the scope of research by including additional classification modeling techniques. The data quality can be enhanced by cross-validation with other databases. Textual commentary about the target firms, including management and analyst quotes, provides additional insight that can enhance the predictive power of the models. Impact on Society: The research provides insights into leveraging emerging technologies to predict acquisitions. The theoretical basis and modeling attributes provide a foundation that can be further expanded to suit specific industries and firms. Future Research: There are opportunities to expand the scope of research in various dimensions by comparing acquisition prediction models across industries and cross-border and domestic acquisitions. Additionally, it is plausible to explore further research by incorporating non-financial data, such as management commentary, to augment the acquisition prediction model.

Aim/Purpose: This study aims to evaluate the success of deep learning in building user profiles for personalized information access. Background: To better express document content and information during the matching phase of the information retrieval (IR) process, deep learning architectures could potentially offer a feasible and optimal alternative to user profile building for personalized information access. Methodology: This study uses deep learning-based models to deduce the domain of the document deemed implicitly relevant by a user that corresponds to their center of interest, and then used predicted domain by the best given architecture with user’s characteristics to predict other centers of interest. Contribution: This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information adapted to their context and their preferences meeting their precise needs. To better express document content and information during this phase, deep learning models are employed to learn complex representations of documents and queries. These models can capture hierarchical, sequential, or attention-based patterns in textual data. Findings: The results show that deep learning models were highly effective for building user profiles for personalized information access since they leveraged the power of neural networks in analyzing and understanding complex patterns in user behavior, preferences, and user interactions. Recommendations for Practitioners: Building effective user profiles for personalized information access is an ongoing process that requires a combination of technology, user engagement, and a commitment to privacy and security. Recommendation for Researchers: Researchers involved in building user profiles for personalized information access play a crucial role in advancing the field and developing more innovative deep-based networks solutions by exploring novel data sources, such as biometric data, sentiment analysis, or physiological signals, to enhance user profiles. They can investigate the integration of multimodal data for a more comprehensive understanding of user preferences. Impact on Society: The proposed models can provide companies with an alternative and sophisticated recommendation system to foster progress in building user profiles by analyzing complex user behavior, preferences, and interactions, leading to more effective and dynamic content suggestions. Future Research: The development of user profile evolution models and their integration into a personalized information search system may be confronted with other problems such as the interpretability and transparency of the learning-based models. Developing interpretable machine learning techniques and visualization tools to explain how user profiles are constructed and used for personalized information access seems necessary to us as a future extension of our work.

Aim/Purpose: The objective of this study is to summarize the challenges of Agile Requirements Engineering (Agile RE) in the public sector in republican and constitutional monarchy nations. Additionally, it offers recommendations to address these challenges. Background: Failure of IT projects in the public sector results in financial losses for the state and loss of public trust, often attributed to issues in requirements engineering such as prioritization of user needs and excessive scope of requirements. IT projects can have a higher success rate with Agile RE, but there are also drawbacks. Therefore, this study holds significance by presenting a thorough framework designed to pinpoint and overcome the challenges associated with Agile RE to increase the success rate of IT projects. Methodology: This study employs a Systematic Literature Review (SLR) protocol in the field of software engineering or related domains, which consists of three main phases: planning the review, conducting the review with a snowballing approach, and reporting the review. Furthermore, the authors perform open coding to categorize challenges based on the Agile methodologies adoption factor model and axial coding to map potential solutions. Contribution: The authors assert that this research enriches the existing literature on Agile RE, specifically within the public sector context, by mapping out challenges and possible solutions that contribute to creating a foundation for future studies to conduct a more in-depth analysis of Agile adoption in the public sector. Furthermore, it compares the barriers of Agile RE in the public sector with the general context, leading to the discovery of new theories specifically for this field. Findings: Most challenges related to Agile RE in the public sector are found in the people and process aspects. Project and organizational-related are subsequent aspects. Therefore, handling people and processes proficiently is imperative within Agile RE to prevent project failure. Recommendations for Practitioners: Our findings offer a comprehensive view of Agile RE in the public sector in republican and constitutional monarchy nations. This study maps the challenges encountered by the public sector and provides potential solutions. The authors encourage practitioners to consider our findings as a foundation for adopting Agile methodology in the public sector. Furthermore, this study can assist practitioners in identifying existing barriers related to Agile RE, pinpointing elements that contribute to overcoming those challenges, and developing strategies based on the specific needs of the organizations. Recommendation for Researchers: Researchers have the potential to expand the scope of this study by conducting research in other countries, especially African countries, as this study has not yet encompassed this geographic region. Additionally, they can strengthen the evidence linking Agile RE challenges to the risk of Agile project failure by performing empirical validation in a specific country. Impact on Society: This research conducts a comprehensive exploration of Agile RE within the public sector, serving as a foundation for the successful adoption of Agile methodology by overcoming obstacles related to Agile RE. This study highlights the importance of managing people, processes, projects, and organizational elements to increase the success of Agile adoption in the public sector. Future Research: In the future, researchers should work towards resolving the limitations identified in this study. This study has not provided a clear prioritization of challenges and solutions according to their significance. Therefore, future researchers can perform a Fuzzy Analytical Hierarchical Process (F-AHP) to prioritize the proposed solutions.

This conceptual research aims to connect aspects of learning activities of continuing education for professionals (CPE). The objective is to provide conclusions about modes of professional learning within diversity, equity, inclusion, and belonging (DEIB) training. This interpretation is placed in context relating to the process of professional learning objectives. A CPE DEIB training plan is presented as an example of how to provide continuing professional education to adult learners within a DEIB curriculum (El-Amin, 2020). The purpose of incorporating the foundations of CPE into DEIB training permits organisations to strengthening organisational development and productivity. By connecting the foundations of curriculum design, alignment, assessment and mapping, and research-informed innovation, CPE aims to enhance the effectiveness of organisational DEIB initiatives. A CPE DEIB training plan emphasises the importance of accountability, employee involvement, and effective training to drive DEIB initiatives.

Implementing inquiry in the outdoors introduces many challenges for teachers, some of which can be dealt with using mobile technologies. For productive use of these technologies, teachers should be provided with the opportunity to develop relevant knowledge and practices. In a professional development (PD) program in this design-based research, 24 teachers were involved in adaptation of a learning environment supporting inquiry in the outdoors that included the use of mobile technologies. They first experienced the learning environment as learners, then adapted it for their own use, and finally, enacted the adapted environment with peers. We examined the scope and character of teacher involvement in adaptation, and the consequent professional growth, by analyzing observations, questionnaires, interviews and the adapted learning-environments. Findings indicate that all teachers demonstrated change processes, including changes in knowledge and practice, but the coherence of the learning environments decreased when substantial adaptations were made. Some teachers demonstrated professional growth, as reflected by their implementation of ideas learned in the PD program in their daily practice, long after the PD program had ended. This study demonstrates how the Teachers as Designers approach can support teacher learning and illustrates productive use of scaffolds for teacher growth and professional development.

Aim/Purpose: To develop a framework for utilizing Mobile Assisted Language Learning (MALL) to assist non-native English migrant women to acquire English vocabulary in a non-formal learning setting. Background: The women in this study migrated to Australia with varied backgrounds including voluntary or forced migration, very low to high levels of their first language (L1), low proficiency in English, and isolated fulltime stay-at-home mothers. Methodology: A case study method using semi-structured interviews and observations was used. Six migrant women learners attended a minimum of five non-MALL sessions and three participants continued on and attended a minimum of five MALL sessions. Participants were interviewed pre- and post-sessions. Data were analysed thematically. Contribution: The MALL framework is capable of enriching migrant women’s learning experience and vocabulary acquisition. Findings: Vocabulary acquisition occurred in women from both non-MALL and MALL environment; however, the MALL environment provided significantly enriched vocabulary learning experience. Future Research: A standardised approach to measure the effectiveness of MALL for vocabulary acquisition among migrant women in non-formal setting