Systematic Literature Review Guidelines Research Articles

Agroecology and resilience of smallholder food security: a systematic review

Multiple covariate shocks such as the COVID-19 pandemic, the Russia–Ukraine conflict, and pre-existing climate shocks pose serious threats to smallholder livelihoods. The cascading effects of these multiple shocks, including rising prices of fertilizers and food imports, have rekindled interest in the call for a policy shift toward agroecology. Agroecology in this study is defined as a set of practices based on ecological principles of diversity, synergy, and nutrient cycling of agroecosystems, which are capable of enhancing the resilience of smallholder food security while providing ecosystem services. Proponents of the agroecology paradigm argue that it is more sustainable and resilience-enhancing. Yet, the nexus among agroecology, resilience, and food security is less understood in the literature. Therefore, this study aimed to review the existing literature to examine how agroecology could enhance the resilience and food security of smallholders. A systematic literature search was performed on Web of Science, Scopus, and PubMed based on three keywords, viz. agroecology, resilience, and food security. Following the 2020 preferred reporting items on systematic review and meta-analysis (PRISMA) guidelines for systematic literature review, 47 articles were retained for the final review. The results provide empirical evidence that supports the potential of agroecological practices in enhancing the resilience and food security of smallholders. This study proposes a framework that links agroecology, resilience, and food security, showing the interplay among all three dimensions of agroecology—the science, policy, and practices—relevant for successful agroecological transitioning or transformation while identifying gaps for further research.

A Systematic Literature Review of Authentic Assessment in K-12 ESL/EFL Education

This research offers an extensive review and analysis of the use of authentic assessment in K-12 ESL/EFL education. The study follows the PRISMA 2020 statement guidelines for systematic literature reviews, investigating peer-reviewed articles from the SCOPUS, WOS, and ERIC databases (2013-2022). The samples comprised teachers, students, and K-12 education documents; non-eligible criteria were excluded. Out of numerous potential studies, 19 were deemed fitting for the review. The findings indicate growing research interest in authentic assessment, with one publication per year minimum since 2015, and notable contributions from Indonesia. Most of the studies (74%) adopted qualitative designs and utilized different authentic assessment types, such as role play, oral interviews, projects, and portfolios. Key factors affecting the implementation included teacher attributes (assessment literacy, language proficiency, support, time), student attributes (motivation, reflection, time, ability), resources (assessment tools, textbooks, guidebooks, teaching aids), and environmental aspects (class size). The review provides valuable insights for teachers aiming to apply suitable authentic assessment strategies and underlines the importance of considering these factors in lesson planning. It emphasizes the need for more research on teachers' assessment literacy and their experiences in employing authentic assessment in K-12 ESL/EFL education, which is currently an underexplored area.

Climate change impact on food security: A review

Countries all over the globe are facing climate change. Global warming is a real problem that occurs and affects food production. Precipitation and temperature rise are causes of the changes observed in this study. This study examines the relationship between food security level due to climate change. To provide further clarity, a systematic literature review (SLR) towards the impacts of climate change was conducted to identify the extent of its impacts on food security and to identify the extent of its impacts on the level of food security and research gaps. This systematic review identifies and analyzes documents on the impact of climate change on the level of food security in terms of the impact of climate change, the methods used to analyze climate change, and the available climate change adaptation policies. Following SLR guidelines, Google Scholar is the main database. This research can broaden our knowledge about the impacts of climate change and the role we can play in maintaining food security.

Data Augmentation and Deep Learning Methods in Sound Classification: A Systematic Review

The aim of this systematic literature review (SLR) is to identify and critically evaluate current research advancements with respect to small data and the use of data augmentation methods to increase the amount of data available for deep learning classifiers for sound (including voice, speech, and related audio signals) classification. Methodology: This SLR was carried out based on the standard SLR guidelines based on PRISMA, and three bibliographic databases were examined, namely, Web of Science, SCOPUS, and IEEE Xplore. Findings. The initial search findings using the variety of keyword combinations in the last five years (2017–2021) resulted in a total of 131 papers. To select relevant articles that are within the scope of this study, we adopted some screening exclusion criteria and snowballing (forward and backward snowballing) which resulted in 56 selected articles. Originality: Shortcomings of previous research studies include the lack of sufficient data, weakly labelled data, unbalanced datasets, noisy datasets, poor representations of sound features, and the lack of effective augmentation approach affecting the overall performance of classifiers, which we discuss in this article. Following the analysis of identified articles, we overview the sound datasets, feature extraction methods, data augmentation techniques, and its applications in different areas in the sound classification research problem. Finally, we conclude with the summary of SLR, answers to research questions, and recommendations for the sound classification task.

What motivates consumers to be in line with online shopping?: a systematic literature review and discussion of future research perspectives

PurposeThis study conducts a systematic literature review to synthesize the extant literature primarily on “online shopping consumer behavior” and to gain insight into “What drives consumers toward online shopping”.Design/methodology/approachThe authors followed guidelines for systematic literature reviews with stringent inclusion and exclusion criteria. The review is based on 79 research papers published from 2000 to 2020 in 21 reputed peer-reviewed international journals. The papers were analyzed and synthesized based on their defining characteristics, methodologies, major constructs and themes addressed.FindingsThe literature synthesis indicated that consumers have to make a trade-off between 11 perceived benefits and six perceived sacrifices to improve their net perceived value before making the final decision to adopt online shopping. It is important to decode these factors as they could improve both the functional and recreational value of the shopping experience for online consumers, resulting in an improvement in conversion rates from a prospect to the final purchase at e-stores. This could improve turnover as well as profits for the e-tailers.Originality/value This study pioneers to consolidate these factors through the lens of the value adoption model. This study also suggests insightful directions for further research perspectives in the online context from both consumers' and retailers' perspectives.

The role of digital technologies to unleash a green recovery: pathways and pitfalls to achieve the European Green Deal

PurposeThe article aims to concern identification and development of pathways for a green recovery process post pandemic taking into account the role of digital technologies for unleashing the policies planned within the European Green Deal (EGD).Design/methodology/approachThe study is based on a systematic literature review (SLR). The electronic databases Scopus and Web of Science (WoS) were surveyed. The authors followed the SLR guidelines laid down by Tranfield et al. (2003) and the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) framework and 65 articles were found eligible after thorough reading and inclusion in the analysis.FindingsThe article presents an innovative framework containing the digital technologies and their roles in enabling the achievement of the EGD policies and the barriers to their adoption.Originality/valueThe proposed framework would guide organizations and policymakers' decisions to pursue a pathway in which a green recovery is possible, mainly after the consequences of the current pandemic, considering the pitfalls of the journey. The article is original as it provides an up-to-date guidance toward an emerging theme, which is a green recovery economy including a net-zero carbon worldwide target.

Examining the needs to adopt big data analytics in B2B organizations: development of propositions and model of needs

PurposeBig data analytics (BDA) is becoming a strategic tool to harness data to achieve business efficiencies. While business-to-customer organizations have adopted BDA, its adoption in business-to-business (B2B) has been slow, raising concerns about the lack of understanding of the need to adopt BDA. Little knowledge exists on the subject and the purpose of this study is to examine BDA adoption needs among B2B organizations.Design/methodology/approachA systematic literature review (SLR) following the six-step SLR guidelines of Templier and Paré (2015) involved 1,051 articles, which were content analyzed.FindingsThe authors offer two-pronged findings. First, on the basis of the SLR, the authors develop a new four-category classification scheme of needs to adopt BDA and present a consolidated review of the current knowledge base along with these categories (i.e. innovation, operational efficiency, customer satisfaction and digital transformation). Second, underpinned by the theory of organizational motivation and literature evidence, the authors develop propositions and a corresponding model of BDA adoption needs. The authors show that BDA adoption among B2B organizations is driven by the need to augment customer lifetime value, champion the change, improve managerial decision cycle-time, tap into social media benefits and align with market transformation.Research limitations/implicationsThe results facilitate theory development as the study creates a new classification scheme of needs and a model of needs to adopt BDA in large B2B organizations.Practical implicationsThe findings will serve as a guideline framework for managers to examine their BDA adoption needs and strategize its adoption.Originality/valueThe study develops a new four-category classification scheme for understanding B2B organizations’ needs to adopt big data analytics. The study also develops a new model of needs which will serve as a stepping stone for the development of a theory of needs of technology adoption.

What have we learnt from the challenges of (semi‐) automated requirements traceability? A discussion on blockchain applicability

Over the last 3 decades, researchers have attempted to shed light into the requirements traceability problem by introducing tracing tools, techniques, and methods with the vision of achieving ubiquitous traceability. Despite the technological advances, requirements traceability remains problematic for researchers and practitioners. This study aims to identify and investigate the main challenges in implementing (semi-)automated requirements traceability, as reported in the recent literature. A systematic literature review was carried out based on the guidelines for systematic literature reviews in software engineering, proposed by Kitchenham. We retrieved 4530 studies by searching five major bibliographic databases and selected 70 primary studies. These studies were analysed and classified according to the challenges they present and/or address. Twenty-one challenges were identified and were classified into five categories. Findings reveal that the most frequent challenges are technological challenges, in particular, low accuracy of traceability recovery methods. Findings also suggest that future research efforts should be devoted to the human facet of tracing, to explore traceability practices in organisational settings, and to develop traceability approaches that support agile and DevOps practices. Finally, it is recommended that researchers leverage blockchain technology as a suitable technical solution to ensure the trustworthiness of traceability information in interorganisational software projects.

Processes, challenges and recommendations of Gray Literature Review: An experience report

Systematic Literature Review (SLR), as a tool of Evidence-Based Software Engineering (EBSE), has been widely used in Software Engineering (SE). However, for certain topics in SE, especially those that are trendy or industry driven, academic literature is generally scarce and consequently Gray Literature (GL) becomes a major source of evidence. In recent years, the adoption of Gray Literature Review (GLR) or Multivocal Literature Review (MLR) is rising steadily to provide the state-of-the-practice of a specific topic where SLR is not a viable option. Although some SLR guidelines recommend the use of GL and several MLR guidelines have already been proposed in SE, researchers still have conflicting views on the value of GL and commonly accepted GLR or MLR studies are generally lacking in terms of publication. This experience report aims to shed some light on GLR through a case study that uses SLR and MLR guidelines to conduct a GLR on an emerging topic in SE to specifically answer the questions related to the reasons of using GL, the processes of conducting GL, and the impacts of GL on review results. We retrospect the review process of conducting a GLR on the topic of DevSecOps with reference to Kitchenham’s SLR and Garousi’s MLR guidelines. We specifically reflect on the processes we had to adapt in order to tackle the challenges we faced. We also compare and contrast our GLR with existing MLRs or GLRs in SE to contextualize our reflections. We distill ten challenges in nine activities of a GLR process. We provide reasons for these challenges and further suggest ways to tackle them during a GLR process. We also discuss the decision process of selecting a suitable review methodology among SLR, MLR and GLR and elaborate the impacts of GL on our review results. Although our experience on GLR is mainly derived from a specific case study on DevSecOps, we conjecture that it is relevant and would be beneficial to other GLR or MLR studies. We also expect our experience would contribute to future GLR or MLR guidelines, in a way similar to how SLR guidelines learned from the SLR experience report a dozen years ago. In addition, other researchers may find our decision making process useful before they conduct their own reviews.

Efficient Automated Processing of the Unstructured Documents Using Artificial Intelligence: A Systematic Literature Review and Future Directions

The unstructured data impacts 95% of the organizations and costs them millions of dollars annually. If managed well, it can significantly improve business productivity. The traditional information extraction techniques are limited in their functionality, but AI-based techniques can provide a better solution. A thorough investigation of AI-based techniques for automatic information extraction from unstructured documents is missing in the literature. The purpose of this Systematic Literature Review (SLR) is to recognize, and analyze research on the techniques used for automatic information extraction from unstructured documents and to provide directions for future research. The SLR guidelines proposed by Kitchenham and Charters were adhered to conduct a literature search on various databases between 2010 and 2020. We found that: 1. The existing information extraction techniques are template-based or rule-based, 2. The existing methods lack the capability to tackle complex document layouts in real-time situations such as invoices and purchase orders, 3. The datasets available publicly are task-specific and of low quality. Hence, there is a need to develop a new dataset that reflects real-world problems. Our SLR discovered that AI-based approaches have a strong potential to extract useful information from unstructured documents automatically. However, they face certain challenges in processing multiple layouts of the unstructured documents. Our SLR brings out conceptualization of a framework for construction of high-quality unstructured documents dataset with strong data validation techniques for automated information extraction. Our SLR also reveals a need for a close association between the businesses and researchers to handle various challenges of the unstructured data analysis.

SURG-37. SYSTEMATIC REVIEW OF GAMMA-KNIFE RADIOSURGERY AND MICROSURGICAL RESECTION FOR BRAINSTEM CAVERNOUS MALFORMATIONS

Abstract BACKGROUND Although microsurgical resection (MR) remains the gold-standard for the treatment of symptomatic cavernous malformations, some authors have proposed the use of radiosurgical Gamma-Knife Surgery (GKS) for lesions that are deep or eloquent, such as those located in the brainstem. OBJECTIVE Here were analyze the literature regarding patient outcomes following MR or GKS for brain stem cavernous malformations. METHODS This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic literature review. A database search of PubMed, Scopus, Embase, and Web of Science was conducted in September 2019. This review included studies evaluating the outcomes of MR or GKS for cavernous malformations located in the brainstem. RESULTS Gross total resection was achieved in the majority of patients and effectively eliminated the risk of recurrent hemorrhage from the operative lesion in studies following the outcomes of MR. GKS reduces the annual hemorrhage rate for patients, although it does not eliminate the cavernous malformation. Both treatment modalities were effective in reducing prior symptomatology. Unlike resection, GKS only reduces the risk of future hemorrhage and does prevent it. CONCLUSIONS Both MR and GKS can improve or stabilize symptoms in patients. However, the therapeutic benefit of GKS may take months to years to take full-effect, resulting in a potential for subsequent hemorrhagic events. MR remains the best treatment option due to its ability to eliminate future bleeding events entirely and should be performed whenever gross total resection is possible.

Issues in reporting of systematic review methods in health app-focused reviews: A scoping review.

No guidelines exist for the conduct and reporting of manuscripts with systematic searches of app stores for, and then appraisal of, mobile health apps ('health app-focused reviews'). We undertook a scoping review including a systematic literature search for health app-focused reviews describing systematic app store searches and app appraisal, for apps designed for patients or clinicians. We created a data extraction template which adapted data elements from the PRISMA guidelines for systematic literature reviews to data elements operationalised for health app-focused reviews. We extracted the data from included health app-focused reviews to describe: (1) which elements of the adapted 'usual' methods of systematic review are used; (2) methods of app appraisal; and (3) reporting of clinical efficacy and recommendations for app use. From 2798 records, the 26 included health app-focused reviews showed incomplete or unclear reporting of review protocol registration; use of reporting guidelines; processes of screening apps; data extraction; and appraisal tools. Reporting of clinical efficacy of apps or recommendations for app use were infrequent. The reporting of methods in health app-focused reviews is variable and could be improved by developing a consensus reporting standard for health app-focused reviews.

Stress, Anxiety, and Depression as Precipitants of Infertility: A Comprehensive Literature Review

Infertility is a pressing public health issue. Psychosocial factors, including stress, anxiety, and depression, have been associated with chronic health conditions and reproductive dysfunction. However, these factors have been studied primarily as concurrent with or resulting from infertility. We used PRISMA guidelines for systematic literature reviews to identify 29 articles for critical review and graded nine for strength of findings. Despite methodological limitations across studies, findings indicate that stress may be associated with subsequent infertility in women; results for anxiety and depression were equivocal. Future researchers should focus on non-clinic-based prospective studies to better understand these associations in the general population.

Neighbourhood collective efficacy and protective effects on child maltreatment: A systematic literature review

Research within the community-based child protection approach has used the neighbourhood collective efficacy theory of social disorganisation to focus on investigating the social conditions and processes that facilitate residents' ability to intervene or protect children from parental maltreatment. However, much of the research into the protective effects of neighbourhood collective efficacy on child maltreatment has yielded mixed results. In a review of empirical studies published between 2008 and 2019, we investigated the sources of these mixed findings and the pathways through which neighbourhood collective efficacy could protect children from parental maltreatment. Following the PRISMA guidelines for systematic literature reviews yielded 21 empirical research articles on the subject that were critically examined in line with the theoretical underpinning and research questions. Evidence suggests both direct and sequential pathways in which increased social cohesion and informal social control (ISC) protect against parents' maltreatment behaviours. Higher levels of neighbourhood social cohesion were found to be a potential primary preventive strategy against risk factors for maltreatment. The use of ISC measures from the traditional collective efficacy scale account for the mixed findings and limited research on the direct and indirect forms of ISC. Moreover, the transactional processes posited by collective efficacy theory that link neighbourhood social cohesion to ISC have yet to be examined and confirmed with respect to child maltreatment. Studies addressing these theoretical and methodological gaps are encouraged, in particular, studies examining ISC dimensions using item measures of specific residents' actions within child maltreatment behaviours. The results provide implications for community-based child protection practice, in terms of promoting cultural norms and values that foster social cohesion and facilitate ISC interventions within neighbourhoods.

Systematic Literature Review of Smart Home Monitoring Technologies Based on IoT for the Elderly

Smart home technology implementation remains an essential aspect of Internet of Things (IoT). It provides needed living support and convenience for elderly people in society. Despite the remarkable achievements in smart home monitoring technology studies, a systematic literature review (SLR) on smart home technology implementation is lacking. There is a limited number of SLR studies on smart home monitoring technology. Therefore, the current study assesses the literature to collect the evidence regarding studies on smart home monitoring technology implantation. An SLR method involving a manual search was applied to review the articles published from January 2010 to December 2019. To carefully classify these articles accordingly, we applied certain quality assessment criteria. Out of 73 relevant primary studies, only 3% were identified to have applied comprehensive SLR guidelines. Seven percent of the relevant studies were identified to have applied the SLR guidelines in a strongly moderately acceptable manner, but they were not completely comprehensive, whereas 8% of the primary studies applied the SLR guideline in a fairly acceptable manner. This manuscript therefore encourages researchers working on SLR studies on smart home technology to apply comprehensive SLR guidelines that takes into account the quality standard.

Systematic Literature Review of Predictive Analysis Tools in Higher Education

The topic of predictive algorithms is often regarded among the most relevant fields of study within the data analytics discipline. They have applications in multiple contexts, education being an important one of them. Focusing on higher education scenarios, most notably universities, predictive analysis techniques are present in studies that estimate academic outcomes using different kinds of student-related data. Furthermore, predictive algorithms are the basis of tools such as early warning systems (EWS): applications able to foresee future risks, such as the likelihood of students failing or dropping out of a course, and alert of such risks so that corrective measures can be taken. The purpose of this literature review is to provide an overview of the current state of research activity regarding predictive analytics in higher education, highlighting the most relevant instances of predictors and EWS that have been used in practice. The PRISMA guidelines for systematic literature reviews were followed in this study. The document search process yielded 1382 results, out of which 26 applications were selected as relevant examples of predictors and EWS, each of them defined by the contexts where they were applied and the data that they used. However, one common shortcoming is that they are usually applied in limited scenarios, such as a single course, evidencing that building a predictive application able to work well under different teaching and learning methodologies is an arduous task.

Systematic literature review of preprocessing techniques for imbalanced data

Data preprocessing remains an important step in machine learning studies. This is because proper preprocessing of imbalanced data can enable researchers to reduce defects as much as possible, which, in turn, may lead to the elimination of defects in existing data sets. Despite the remarkable achievements that have been accomplished in machine learning studies, systematic literature reviews of imbalanced data preprocessing techniques are lacking. Consequently, there are a limited number of systematic literature review studies on imbalanced data preprocessing. In this study, the authors assess the existing literature to identify the key issues related to data quality and handling and to provide a convenient collection of the techniques used to address these issues when performing data preprocessing. They applied a systematic literature review method involving a manual search to select articles published from January 2010 to September 2018 for review. The qualities of the existing studies were assessed using certain quality assessment criteria. Of the 118 relevant studies found, only 2% were identified as having been conducted following systematic literature review guidelines. This study, therefore, calls for more systematic literature review studies on data preprocessing to improve the quality of the data applied in machine learning studies.

Mempertahankan keaslian arsip elektronik di era digital berdasarkan tinjauan literatur sistematis

Introduction. This research aimed to understand efforts should be taken so that the authenticity of electronic records can be maintained in the digital environment. Data Collection Method. This research used a systematic literature review published by scientific journals from January 2010 to April 2019 derived from electronic information sources subscribed by the University of Indonesia Library. The results of this review are reported using guidelines for Systematic Literature Review (SLR) which has three stages, namely planning, implementation, and reporting.Analysis Data. Descriptive quantitative was employed to analyze the data by using simple statistic application (Microsoft Office Excel 2007). Results and Discussion. The results indicated that there are 18 literatures (3%) of the total search results of 561 relevant literatures discussing electronic records and ways to maintain their authenticity in digital era. There were 12 articles providing sufficient information about this matter.Conclusion. The majority of the articles mentioned that to maintain the authenticity of electronic archives in digital era must be supported by policy makers such as the government. In addition, the knowledge and skills of archival managers, as well as appropriate technology are also needed.

Systematic Literature Review on Penetration Testing for Mobile Cloud Computing Applications

Mobile cloud computing (MCC) enables mobile devices to exploit seamless cloud services via offloading, and has numerous advantages and increased security and complexity. Penetration testing of mobile applications has become more complex and expensive due to several parameters, such as the platform, device heterogeneity, context event types, and offloading. Numerous studies have been published in the MCC domain, whereas few studies have addressed the common issues and challenges of MCC testing. However, current studies do not address MCC and penetration testing. Therefore, revisiting MCC and penetration testing domains is essential to overcoming the inherent complexity and reducing costs. Motivated by the importance of revisiting these domains, this paper pursues two objectives: to provide a comprehensive systematic literature review (SLR) of the MCC, security and penetration testing domains and to establish the requirements for penetration testing of MCC applications. This paper has systematically reviewed previous penetration testing models and techniques based on the requirements in Kitchenham's SLR guidelines. The SLR outcome has indicated the following deficiencies: the offloading parameter is disregarded; studies that address mobile, cloud, and web vulnerabilities are lacking; and a MCC application penetration testing model has not been addressed by current studies. In particular, offloading and mobile state management are two new and vital requirements that have not been addressed to reveal hidden security vulnerabilities, facilitate mutual trust, and enable developers to build more secure MCC applications. Beneficial review results that can contribute to future research are presented.

Guidelines for including grey literature and conducting multivocal literature reviews in software engineering

ContextA Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and –practice in a given area. MLRs are popular in other fields and have recently started to appear in software engineering (SE). As more MLR studies are conducted and reported, it is important to have a set of guidelines to ensure high quality of MLR processes and their results. ObjectiveThere are several guidelines to conduct SLR studies in SE. However, several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. MethodTo develop the MLR guidelines, we benefit from several inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. We took the popular SLR guidelines of Kitchenham and Charters as the baseline and extended/adopted them to conduct MLR studies in SE. All derived guidelines are discussed in the context of an already-published MLR in SE as the running example. ResultsThe resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of experience-based recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. ConclusionHaving been developed on the basis of several types of experience and evidence, the provided MLR guidelines will support researchers to effectively and efficiently conduct new MLRs in any area of SE. The authors recommend the researchers to utilize these guidelines in their MLR studies and then share their lessons learned and experiences.