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The purpose of this paper is to identify various risks in the power distribution supply chain and further to prioritize the risk variables and propose a model to the power distribution industry for managing the interruptions in its supply chain. To accomplish this objective, a case of a major power distribution company has been considered.

Failure mode and effects analysis (FMEA) analysis has been done to identify the potential failure modes, their severity, and occurrence and detection scores. Then an interpretive structural model (ISM) has been developed to identify and understand the interrelationships among these enablers followed by MICMAC analysis, to classify the risk variables in four quadrants based on their driving and dependency powers.

The results of this study exhibit that technical failure in the information and technology system, the use of improper equipment, poor maintenance and housekeeping in the internal operations are the major risk drivers. Exposure to live wires and commercial loss in power supply has strong dependence power.

This study is limited to a single power distribution company and not the whole power distribution sector.

This study suggests the managers of the power distribution company develop an initial understanding of the drivers and the dependent powers on the supply chain risks.

Through prioritization, identification of drivers and the dependent risks, the losses in the power distribution supply chain can be minimized.

Various failures in the power distribution have been studied in the past, but they have not investigated the supply chain risks in the power distribution of a power distribution company.

In spite of the popularity of learning analytics (LA) in higher education institutions (HEIs), the success rate and value gained through LA projects is still little and unclear. The existing research on LA focusses more on tactical capabilities rather than its effect on organizational value. The key questions are what are the expected benefits for the institution? And how the investment in LA can bring tangible value? In this research, the authors proposed a value realization framework from LA extending the existing framework of information technology value.

The study includes a detailed literature review focusing on the importance, existing frameworks and LA adoption challenges. Based on the identified research gap, a new framework is designed. The framework depicts the several constructs and their relationships focusing on strategic value realization. Furthermore, this study includes three case studies to validate the framework.

The framework suggests that leveraging LA for strategic value demands adequate investment not only in data infrastructure and analytics but also in staff skill training and development and strategic planning. Universities are required to measure the strategic role of LA and spend wisely in quality data, analytical tools, skilled staff who are aware of the latest technologies and data-driven opportunities for continuous improvement in learning.

The framework permits education leaders to design better strategies for attaining excellence in learning and teaching, and furnish learners with new data to settle on the most ideal decisions about learning. The authors believe that the appropriation of this framework and consistent efficient interest in learning analytics by the higher education area will prompt better results for learners, colleges and more extensive society. The research also proposes two approaches and eleven research agendas for future research based on the framework. The first is based on the constructs and their relationships in LA value creation, whereas the later one focusing on identifying problems associate with it.

The purpose of this paper is to explore the actual walking distance to public transport (PuT) stations and to report passenger perceptions on route choice.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). It can determine the interrelation between the accessibility of the transit service and evaluation on walking distance acceptance. Statistical analysis and geo-spatial approach were completed for obtaining major findings.

Statistical and geo-spatial analysis shows that respondents living in low-density areas walk longer than residents living in nearby inner city areas. In terms of PuT modes, residents walk longer for suburban train and subway/metro (U-Bahn) than for bus/tram services. Transit users accept a longer walking distance to reach a train station than other PuT modes and they choose the most direct and quickest route to reach PuT stations.

Findings of this study would help to formulate future strategies and standards for the sustainable planning of public transportation systems in the context of Munich and many other cities around the globe with similar conditions. However, future research should be conducted using a large-scale survey for evaluating the comprehensive picture of walking patterns to PuT stations. Accessibility to PuT stations can also be modeled and evaluated by adopting open data and voluntary social media information. Unfortunately, this study only presents a partial evaluation of walking focused on accessibility at selected PuT stations in different settings of the urban fabric.

This empirical study can be considered as an initial finding in the favor of the city transport authority to provide a design scale for improved accessibility of transit users; however, further investigation should be conducted using a large-scale survey for evaluating the comprehensive walking patterns.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). Findings of this study would help to formulate future strategies and standard for the sustainable planning of the public transportation system in the context of Munich and many other cities in the globe with similar conditions.

The purpose of this paper is to present a high accuracy path following method for low-cost fixed-wing UAVs.

The original vector field (VF) algorithm is condensed. A spatial integration mechanism is added to the existing VF and nonlinear guidance law, aiming to decrease steady-state cross-track-error and cope with long-term disturbance.

Numerical simulations show the proposed method could diminish steady-state cross-track-error effectively. Test flights show the proposed method is applicable on low-cost fixed-wing UAVs.

The path following accuracy shown in simulations and test flights indicates the proposed method could be deployed in scenarios including inflight rendezvous, formation, trafficway take-off and landing.

This paper provides an improved high-accuracy path following method for low-cost fixed-wing UAVs.

The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.

The case was an application of a market demand and supply mechanism and its impact on the product’s price and focus on the following objectives:▪ Analyze the vegetable market in India and the challenges faced by the farmers (tomatoes) using demand and supply concepts.▪ Examine the impact of price elasticity on the revenue of the farmers.▪ Assess the challenges faced by the government in controlling prices of vegetables and food inflation.▪ Evaluate diversification strategies in agriculture to mitigate risk.

The market for tomatoes was highly cyclical because of erratic rainfall, and farmers went through a difficult time, especially when the prices fell below the cost of production. They moved out for crops that had stable prices. They expected government support for price stability. Government and policymakers considered price fluctuations a short-term phenomenon that required limited interventions when prices were high. This case was about Dilip, a farmer who was into farming tomatoes on a large scale in Karnataka, India. He was facing a dilemma as to whether he had to continue or move to other crops because of the low price of tomatoes in May 2023 or to diversify into some small but related business. He was worried at the same time, curious to understand the volatility in the prices of tomatoes, government responses, risks and returns associated with the cultivation of this crop and Agri-supply chain. Based on his understanding, he should make decisions to continue or diversify into some other farming or related business.

This case was written for microeconomics and managerial economics of undergraduate and postgraduate students. This case demonstrates the application of the demand and supply mechanism for a perishable product such as tomatoes. Price fluctuations are common in these markets because of various uncontrollable factors such as rain, pests and natural calamities. The case could show the relationship between the firm’s elasticities and revenue. This case also highlights the policy constraints in controlling the prices in the short run. This case could also be used for understanding macroeconomic concepts such as food inflation and its impact on general price inflation. The students or target audience with a background in the functioning of the markets could very well relate to the concepts discussed.

Teaching notes are available for educators only.

CSS: Entrepreneurship (3); Management Science (7).

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

A vision-assisted fuzzy adaptive sliding mode controller is presented in this research and implemented on a nonlinear helicopter model, which is about to land on a moving ship. Stabilization of the dynamics and tracking the landing path are required, at the same time. This study aims to take one step closer to fully autonomous landing, which is a growing trend.

An integrated guidance and control is considered for the model helicopter. A fuzzy logic is designed to adaptively choose the best control parameters for the sliding mode controller and solve the challenge of parameter tuning. A self-organizing matrix consisting of fuzzy sliding mode parameters is formed instead of a single parameter with the goal of enhancing controller tracking capability. A simple, precise and fast image recognition system based on OpenCV is used to detect the proper point for descending without getting any special data from the ship and by only using a general “H” sign.

The problem is simulated under intense disturbances, while the approach and landing performances are acceptable. Controller performance is compared and validated. Simulation results show the robustness, agility, stability and outperformance of the proposed controller.

The novelty of this paper is the designed procedure for using a simple image recognition system in the process of autonomous ship-landing, which does not use any special data sent from the ship. Besides, an improved nonlinear controller is designed for integrated guidance and control in this specific application.

The purpose of this paper is to develop a multi‐user electronic bill presentment and payment (EBPP) model that would enhance the present billing systems as well as overcome the problems of periodic generation of billing reports and mail volumes.

The paper evaluates three existing models of EBPP: Biller‐direct, consolidation, and invited pull models and identifies their limitations. Then, the thin consolidation model approach is modified by developing an Extensible Hypertext Markup Language based architecture that is capable of consolidating billing reports from a variety of disparate heterogeneous sources. The modified model is implemented using two case studies.

The modified consolidation model of the EBPP enhances quick subsequent notification of bills to the consumer for goods or services previously rendered. In the model, a user could pay for multiple services rendered by companies; this in turn overcomes mail volumes.

This paper develops a data integration and unification architecture that will allow billing reports from multiple billers to be integrated into a unified database.

The case describes the performance evaluation system that has been put in place by Ravi Kumar, the MD to ensure that Oystar Hassia is able to design, deliver, service, sell its packaging machines seamlessly in all parts of the world. The performance evaluation system is periodic, regular, able to take track the progress of the people within the system. The benefits accrued from performance evaluation system are also detailed in this case.