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The purpose of this study is to systematically examine the existing literature published on the circulation methods used in academic libraries and to discuss a proposed model for the self-check-in and check-out methods using quick response (QR) codes.

A systematic literature review (SLR) provided a complete overview of circulation systems used in academic libraries for the last more than 140 years. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) method for SLR was used. Several databases such as ProQuest, Emerald, Library and Information Science Abstracts, EBSCO and Google Scholar were searched. Out of 277 papers retrieved in the search, 43 most relevant papers were taken up for the SLR. These were classified into four themes based on the systems of circulation used, namely, manual (5), mechanized (13), automated (5) and networked system (20). Based on the findings of the SLR, a model of circulation system in which QR code technology has been used.

The result of SLR identified 33 systems used in above mentioned four groups. Among this, a large number 48.48% of mechanized systems were found. Each system has limitations either because of devices used or of technology. The present study proposes a QR code-based model at the circulation desk, for which a prototype of Android app has been designed. This would help to initiate the new “self-services” facility to users at the circulation desk.

The proposed model, after its successful implementation, can be adopted by academic libraries. Guidelines and a graphical representation of this study can be used by any researcher for further experimentation.

To the best of the authors’ knowledge, this is the first kind of study in which a QR code-based Android app model has been proposed for library circulation records.

The purpose of this study is to propose an objective and efficient method for assessing credit risk by introducing and investigating to a greater extent the applicability of credit scoring models in the Jordanian banks and to what range they can be used to achieve their strategic and business objectives.

The research methodology comprises two phases. The first phase is the model development. Three modeling techniques are used to build the scoring models, namely, logistic regression (LR), artificial neural network (NN) and support vector machine (SVM), and the best performing model is selected for next stage. The second phase is two-fold: linking the credit expert knowledge in a way that can enhance the outcomes of the scoring model and a profitability test to explore if the selected model is efficient in meeting banks’ strategic and business objectives.

The findings showed that LR model outperformed both ANN and SVM across various performance indicators. The LR model also fits best with achieving the bank’s strategic and business objectives.

To the best of the authors’ knowledge, this study is the first that applied several modeling and classification techniques for Jordanian banks and calibrated the best model in terms of its strategic and business objectives. Furthermore, credit experts’ knowledge was engaged with the scoring model to determine its efficiency and reliability against the sole use of an automated scoring model in the hope to encourage the application of credit scoring models as an advisory tool for credit decisions.

To assess the state of supply chain management (SCM) research in India and to understand the research trends and methodologies used. The present study also aims to create a taxonomy of the subject areas researched in India.

The present study employed the systematic literature review methodology. Literature from 395 peer journal papers in 67 leading journals over a 20-year period (2000–2020 Quarter-1) was comprehensively reviewed and assessed.

SCM research in India started around the year 2000. The quantum of research was low (single digit) until 2010. There has been steady growth over the last decade, and over 50% of the total papers up until now has been published in the last four years. The present study created a three-tiered taxonomy of the subject areas and classified the papers as per it. The first tier (level-1) has seven categories (SCM strategy, network design, SCM processes and integration, IT systems, skills, performance measurement and others). A perusal of the newly created taxonomy revealed that, except for a few areas under level-1 categories (such as SCM processes and SCM strategy), the other level-1 categories have not seen much research. Similarly, there is little or no research in a large number of level-2 categories (such as outsourcing strategy, channel strategy, demand management, demand fulfillment, customer relationship management, integrated supply chain planning, new product development, returns, supply chain orientation, performance monitoring, performance improvement, SCM adoption process, SCM implementation issues and quantified benefits of SCM). Methodologically, the rigor of SCM research in India needs improvement.

A comprehensive taxonomy of SCM subject areas researched in India at three cascading levels was created for the first time in the present study. The taxonomy will help provide researchers with a clear understanding of the structure of the subject areas and help in identifying areas where research has been carried out and the subject areas where gaps exist for future research to proceed. The present study also provides an overview of the methodological rigor of SCM research in India and points out some of the limitations that researchers should avoid in future studies.

The purpose of this paper is to examine the likelihood that the presence of the deposit insurance policy encourages risk appetite behavior of banks in Sub-Saharan African (SSA). It argues that financial system stability is not a function of the choice of a deposit insurance scheme, but countries' peculiarities such as quality of institutions and the macroeconomic environment.

The study used the stereotype logit regression model and covers 47 SSA countries. Countries are categorized into two: explicit and implicit DIP scheme.

The study found that corrupt countries are more likely to adopt the implicit policy, while the explicit policy exposes them to credit risk, insolvency, and negative macroeconomic shocks, a reflection of weak institutions and unhealthy competition.

Paucity of substantial local literature on institutional perspective of deposit insurance (DI) constitutes the major limitation of this study.

The sub-region, therefore, faces a conundrum - desiring a deposit insurance scheme, but lacking the required institutions to maintain either a publicly owned regulatory system or the ability to transplant the private club model.

This study contributes to the institutional perspective of DI from SSA institutional perspective.

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.

This study aims to combine information about sea level rise (SLR), the probability distribution of storm surge, a flood damage function and the value of property by elevation along the coast of selected cities to measure expected flood damage. The selected six cities all have nearby long-term tidal stations that can be used to estimate the probability distribution of floods. The model is calibrated to each city. The study then compares the cost of building higher seawalls today along the coast versus the benefit of each wall (the reduction in expected flood damage).

The combination of coastal storms and SLR has led to extensive flood damage across American cities. This study creates a simple generic model that evaluates whether seawalls would be effective at addressing this flooding problem. The paper develops an approach that readily measures the expected flood benefits and costs of alternative coastal seawalls. The approach takes account of near term SLR and the probability distribution of storm surge. The model finds seawalls are effective only in cities where many buildings are in the 25-year flood plain.

Cities with many buildings built on land below 2 m in elevation (the 25-year flood plain) have high expected flood damage from storms and SLR. Cities which already have many buildings in this flood plain would benefit from seawalls. Assuming seawalls are built above the high tide line, the optimal wall height that maximizes net benefits is between 0.9 to 1.2 m. These relatively low seawalls block 70%–83% of expected flood damage in these cities. Fair flood insurance is the least cost strategy for handling the remaining damages that overtop the optimal seawalls.

The analysis evaluates whether or not to build a seawall the length of each city at high tide lines. However, the analysis also finds several long stretches of coast in two cities where a wall is not warranted because there are few vulnerable buildings. Future analyses should consider seawalls in more spatially detailed sections of each city. Each section could then be analyzed independently. Whether or not more complex hydrodynamic models are needed to evaluate coastal resilience planning should also be explored. Alternative solutions such as planned retreat and nature-based solutions should be compared with seawalls in future studies as well.

Cities should be careful to avoid development in the 25-year flood plain because of high expected flood damage. Cities that have low elevation areas subject to frequent flooding should consider seawalls to reduce frequent flooding. Because they are very costly and have low expected benefits, high walls that can stop a one-hundred-year storm are generally not worth building.

The analysis reveals that the most important factor determining the vulnerability of cities along the eastern coastline of the USA is the number of buildings built below 2 m in elevation (the 25-year flood plain). Cities should use zoning to discourage further development in the 25-year flood plain. Cities which already have many buildings in this flood plain would benefit from city-wide seawalls. Assuming these walls are built at mean high-high tide, the optimal height of current seawalls should be relatively modest – averaging about 0.9–1.2 m above ground. Using fair insurance for the remaining risk is less expensive than building taller walls. In particular, the cost of seawalls that protect against a major hurricane surge are over three times the expected benefit and should not be built. As decades pass and observed sea level progresses, seawalls and the boundary of the 25-year flood plain should be reevaluated.

This paper develops a coastal flood model that combines SLR and the probability distribution of storm surges with the value of property by elevation to estimate the expected damage from storm surge. The model is relatively easy to calibrate making it a practical tool to guide city flood planning. The authors illustrate what insights such a model gives about coastal resilience to flooding across six cities along the Eastern US coastline.

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

Study on knowledge-based systems for scientific publications is growing very broadly. However, most of these studies do not explicitly discuss the knowledge management (KM) component as knowledge management system (KMS) implementation. This background causes academic institutions to face challenges in developing KMS to support scholarly publication cycle (SPC). Therefore, this study aims to develop a new KMS conceptual model, Identify critical components and provide research gap opportunities for future KM studies on SPC.

This study used a systematic literature review (SLR) method with the procedure from Kitchenham et al. Then, the SLR results are compiled into a conceptual model design based on a framework on KM foundations and KM solutions. Finally, the model design was validated through interviews with related field experts.

The KMS for SPC focuses on the discovery, sharing and application of knowledge. The majority of KMS use recommendation systems technology with content-based filtering and collaborative filtering personalization approaches. The characteristics data used in KMS for SPC are structured and unstructured. Metadata and article abstracts are considered sufficiently representative of the entire article content to be used as a search tool and can provide recommendations. The KMS model for SPC has layers of KM infrastructure, processes, systems, strategies, outputs and outcomes.

This study has limitations in discussing tacit knowledge. In contrast, tacit knowledge for SPC is essential for scientific publication performance. The tacit knowledge includes experience in searching, writing, submitting, publishing and disseminating scientific publications. Tacit knowledge plays a vital role in the development of knowledge sharing system (KSS) and KCS. Therefore, KSS and KCS for SPC are still very challenging to be researched in the future. KMS opportunities that might be developed further are lessons learned databases and interactive forums that capture tacit knowledge about SPC. Future work potential could identify other types of KMS in academia and focus more on SPC.

This study proposes a novel comprehensive KMS model to support scientific publication performance. This model has a critical path as a KMS implementation solution for SPC. This model proposes and recommends appropriate components for SPC requirements (KM processes, technology, methods/techniques and data). This study also proposes novel research gaps as KMS research opportunities for SPC in the future.

The regulatory framework may be construed as the existence of supporting infrastructure that assists in control, direction/implementation of a proposed course of law, rule or action. The regulatory order is now more formalized, expert-driven, transparent, independent and pervasive across countries and sectors. As a result, regulatory reforms enable markets to function efficiently by providing a supportive environment for increased investment, private sector growth and market-led economic growth. This study aims to review previous literature for understanding the impact of sectoral regulatory framework on sectoral performance.

This paper has adopted a systematic literature review to understand dynamics between the sectoral regulatory framework and sectoral performance. While seven multidisciplinary databases were used to identify 51 research articles, the bibliometric research profiling was executed to broaden academic research.

The results are organized into three broad categories: research context, research area and research methods. The identified articles exhibited association with 12 distinct sectors/industries, with maximum articles belonging to telecom, energy and finance industries. The study has focused on evolution of regulatory studies, impact of regulatory framework on sectoral performance and commonality in regulatory studies. Among the 15 distinct research contexts identified in this systematic literature review (SLR), the highest mapping was registered (from 23 articles) by the research context “impact of regulatory framework on the sector–institutions, infrastructure and performance indicators.”

Public administration researchers are increasingly using mixed methods research approaches to add diverse and novel perspectives on wicked problems. The qualitative approach (grounded theory, action research, phenomenology and participant observations) is appropriate for understanding the native viewpoints of regulatory practitioners and reducing the gap between rigor and relevance.

The study addresses lack of systematic review of articles covering the impact of regulatory framework on sectoral performance encompassing all sectors by, inter alia, collating important bibliometric profiles of the identified articles.

This study aims to examine the effects of levee construction and tropical storms on regional economic growth of a coastal community. The study's goal is to highlight feedbacks important to climate change adaptation in the coastal zone.

The research utilizes a dynamic feedback model that includes coastal engineering, urban economic development, and natural ecosystem response. The model is a tool to help discuss important long‐term issues and to highlight areas of policy intervention. The data for the model come from US Census data, the global DIVA coastal database, and IPCC projections.

The results show urban areas facing elevated levels of exposure because of residents' low understanding of climatic risks. Coastal managers may actually increase long‐term exposure by attempting to protect coastal regions from long‐term sea‐level rise. Coastal defenses lead to a false sense of safety, increasing economic development in the short term, but causing larger economic losses in the long term, especially after a storm. Storm intensity and levee protection are important in determining an “economic tipping point” of long term growth – whether a community continues to grow or faces economic stagnation or decline. If storm damage is large enough, the community passes the tipping point and economic growth never recovers. The presence of levees changes the tipping point dynamic, making communities more resilient as long as there is no levee breach.

Coastal communities face increasing risk from accelerated sea‐level rise and tropical storms. Understanding the long‐term dynamics of protection decisions is important for creating effective adaptation policies.