Journal of Cases on Information Technology

The rapid development of information technology (IT) has enabled digital services to evolve continually and support a growing number of internet-enabled devices, along with user diversity. The end-user anticipation within the smart environments, which are internet-enabled, delivery networks and innovative technologies. What tools/methods can support the collaborative design and effectively choreograph the design process with dynamic knowledge between service designers and service users? The cooperative design is recognizable in the design environment with a collection wide-ranged by co-design methods and tools. In-depth interviews uncover contextually appropriate design process requirements from diverse stakeholder groups. A collection of design tools and methods are selected and implemented within a Web-based co-design platform. Uncovered design requirements are subsequently applied in extending the Double Diamond framework prior to operationalization into a design process blueprint with supporting service design tool selection as the main contributions for this paper.

Wireless sensor networks (WSNs) are used in industrial applications and focused on target coverage and node connectivity based WSNs. The set of sensors and targets is placed in optimal position the target coverage and node connectivity achieving maximum with limited senor nodes. To resolve this problem, the proposed hybrid genetic algorithm combined with lifting wavelet multi-resolution principles for recognizing optimal position for sensors to cover entire targets present in the fields. The hybrid genetic algorithm randomly identifies each sensor position and 2D Haar lifting wavelet transform to improve the quality of target coverage by adjusting node position. The 2D Haar lifting decomposes the population matrix into the optimal position of sensors. Experimental results show the performance of the proposed hybrid genetic algorithm and fast local search method compared with available algorithms improves the target coverage and the number of nodes with varying and fixed sensing ranges with a different region.

Artificial intelligence (AI) is developing and its application is spreading at an alarming rate, and AI has become part of our daily lives. As a matter of fact, AI has changed the way people learn. However, its adoption in the educational sector has been saddled with challenges and ethical issues. The purpose of this study is to analyze the opportunities, benefits, and challenges of AI in education. A review of available and relevant literature was done using the systematic review method to identify the current research focus and provide an in-depth understanding of AI technology in education for educators and future research directions. Findings showed that AI's adoption in education has advanced in the developed countries and most research became popular within the Industry 4.0 era. Other challenges, as well as recommendations, are discussed in the study.

Network routing has a great impact on the efficiency and reliability of the traffic network system in a real-world scenario. To date, achieving network-consistent performance is the main goal of many traffic network research studies. In this research, a mixed strategy game-theory model for network routing is proposed that discovers the optimal strategies that can be adopted by network route players in a network graph. This model has been validated by measuring the model outcomes using quantal response equilibrium (QRE) technique, which explores the players' noisy decisions by comparing the utilized optimal strategies with Nash equilibrium. The experimental results demonstrate that there is an equilibrium with a mixed strategy of a given network.

In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empirically show that, under an OLTP workload, a row-store DBMS sustains a 1000 times higher throughput than a columnar DBMS, whilst OLAP queries are more than 4 times faster on a columnar DBMS. Finally, a reactive streaming ETL pipeline is implemented which connects these two DBMSs. Separate benchmarks show that OLTP events can be streamed to an OLAP database within a few seconds.

Digital transformation since year 2010 has provided a huge worldwide market with digital consultants as top players. Digital transformation is a socio-economic phenomenon subject to lengthy surveys and actual cases on behalf of digital consultants between 2010-2020. By the end of the 2010s, digital transformation management has been reviewed in scientific journals. This is an instrumental case study about digital transformation at PWC, Siemens and Oracle as digital technology providers and consultants. Worldwide digital technology induces digital transformation with the purpose of value creation, motivating companies. Digital consultants are top players. Digital transformation frameworks and digital maturity studies show the dimensions, stages and scales of digital transformation. Roadmaps, programs, projects guide the specific steps from one maturity stage to the target. Business cases are used to compute customer value. Customer value is stipulated in customer contracts in as a service business models. Digital transformation solutions are marketed using these tools.

Along with growing interest and use, the concept of network analysis has taken a new direction to explore data and facts to find existing patterns. The paper highlights the importance of social network analysis in analyzing and mining useful information from the data across various domains. It provides an insight into need, importance and scope of Social Network Analysis. With the use of Social networking tool like NetworkX, data is being represented in the form of graph or network which is then analyzed in a more efficient way making it easier to study the interactions between different persons in Game of thrones and establishing trends existing in a network. A comparative analysis of various centrality measures such as Degree centrality, Betweenness centrality, Closeness centrality, PageRank centrality is performed to explore the features associated to find the most important character of the series based on obtained results.

The use of software in mission critical applications poses greater quality needs. Quality assurance activities are aimed at ensuring such quality requirements of the software system. Antifragility is a property of software that increases its quality as a result of errors, faults, and attacks. Such antifragile software systems proactively accepts the errors and learns from these errors and relies on test-driven development methodology. In this article, an innovative approach is proposed which uses a fault injection methodology to perform the task of quality assurance. Such a fault injection mechanism makes the software antifragile and it gets better with the increase in the intensity of such errors up to a point. A software quality game is designed as a two-player game model with stressor and backer entities. The stressor is an error model which injects errors into the software system. The software system acts as a backer, and tries to recover from the errors. The backer uses a cheating mechanism by implementing software Learning Hooks (SLH) which learn from the injected errors. This makes the software antifragile and leads to improvement of the code. Moreover, the SLH uses a Q-Learning reinforcement algorithm with a hybrid reward function to learn from the incoming defects. The game is played for a maximum of K errors. This approach is introduced to incorporate the anti-fragility aspects into the software system within the existing framework of object-oriented development. The game is run at the end of every increment during the construction of object-oriented systems. A detailed report of the injected errors and the actions taken is output at the end of each increment so that necessary actions are incorporated into the actual software during the next iteration. This ensures at the end of all the iterations, the software is immune to majority of the so-called Black Swans. The experiment is conducted with an open source Java sample and the results are studied selected two categories of evaluation parameters. The defect related performance parameters considered are the defect density, defect distribution over different iterations, and number of hooks inserted. These parameters show much reduction in adopting the proposed approach. The quality parameters such as abstraction, inheritance, and coupling are studied for various iterations and this approach ensures considerable increases in these parameters.

Multimedia case studies are effective constructivist instructional tools that can help to design contextually authentic scenarios while also scaffolding instruction to help students move beyond their current skill and knowledge base. Although there are many advantages of using multimedia case-based learning, there are also many challenges associated with designing technology-enhanced case studies for constructivist learning. The research described herein presents the advantages and challenges that emerged from three unique learning environments in health professional education programs. In each of these environments, a multimedia educational tool (named the multimedia case-based learning sports injury assessment educational tool) was designed to engage students in authentic sport injury case scenarios. Feedback was gathered from multiple stakeholders in each learning context and used to explore the effectiveness of this technology-enhanced pedagogical approach.

Despite recent technological advancements, the slow adoption pattern of digital healthcare promotion programs continues to be a major problem plaguing many healthcare organizations today. The historical teaching case study is indispensable in improving our understanding of the complex and multifaceted nature of contemporary digital healthcare promotion programs. This historical teaching case presents information about e-health, the e-commerce unit of a large multinational healthcare insurance company. The teaching case shows how despite e-health’s ability to persuade a large registered base of users to trial its healthcare promotion programs, over 90% of these registrants discontinued use after a short trial period of using the technology. This historical teaching case focuses on the social challenges involved in persuading users to adopt and continue using e-health’s major healthcare promotion innovation: an online nutrition center. Despite extensive promotions and the use of incentives, less than 10% of the user base adopted and continued to use this healthcare promotion innovation. The case reports on the discontinuance among digital healthcare promotion users despite the intensive efforts to retain them. Students and practitioners will gain insight into the key social challenges involved in achieving a critical mass of users for digital healthcare promotion innovations. The teaching case requires important decisions to be made by students and practitioners about present digital healthcare promotion programs by drawing on inferences from past digital healthcare promotion programs. Finally, this historical teaching case study makes a convincing case for the value of historical insights in informing present day challenges facing contemporary digital healthcare promotion programs.

This research mainly aims to explore the factors that influence users' continuous use of mobile libraries. The findings of this study will provide empirical evidence to help improve the service and information quality of mobile libraries. Moreover, suggestions for optimization are provided with the objective of meeting user demands at its maximum. A theoretical model is constructed to reveal the impact of 11 influencing factors on users' continuous use of mobile libraries. Structural equation modeling is adopted to verify the theoretical model and research hypothesis based on the valid data obtained from a questionnaire survey. The study found that personalized services and information availability have positive impacts on the service quality of mobile libraries. Moreover, perceived mobility and information quality have positive impacts on the perceived usability of mobile libraries. Finally, perceived usability, service quality, and platform stability have significantly positive impacts on the willingness of users to continue usage of mobile libraries.

Despite overwhelmingly positive reviews for decision support systems, the IS literature has produced inconsistent results regarding the role of top management and the effectiveness of these systems. IS researchers are concerned with there being a widening gap between research and practice, leading to the current study, focusing on the relevance of these two constituencies. This study employs the Delphi methodology in relation to Saudi Arabia to investigate the reality of the decision support systems in governmental organizations and the diverse issues related to making effective use of them by increasing the role of top management. The findings revealed that there is an absence of a role for IT in the decision-making process, and that there is a lack of robust data warehouse systems capable of supporting organizations' top management with high-quality information. The study revealed various required reforms of various governmental and institutional arrangements and obligational aspects of the efficiency of decision support systems.

Users of enterprise software are multiple, and their requirements are diverse. Often their specifications are masked by mundane details and at times are vague too. Acknowledging these complexities in requirements engineering, the paper proposes a multistage methodological approach based on Apriori algorithm, a data mining technique. It extracts useful information from the given data on the criteria of mutual association and sufficient frequency. The user requirements captured through interviews and brainstorming are pre-processed for eliminating unnecessary stop words and developing a uniform structure of small stories. Mutual association and occurrence of the requirements are represented through association rules and rule metrics, for example, ‘Lift', ‘Support', and ‘Confidence'. The requirements having strong and moderate association are placed in ‘Top Priority List'; those with nominal, weak, or nil association are placed in ‘Low Priority List'. Gap analysis is employed to validate the defined requirements with respect to stakeholders' expectations. The complete and correct lists of requirements significantly influence the client satisfaction, software development process, and its eventual success.

Today, IT and especially the development of customer-focused software, has become one of the most important elements for a company to remain competitive. The primary purpose of this article is to determine whether it is possible to improve the agile development of a company by adjusting its software development process in terms of cultural, technical, and managerial dimensions. Based on a literature analysis and practical experience in the company, different influencing factors and parameters, which affect the value creation throughout the software development process of a company were derived and clustered. Out of these clusters, a framework (Agile Method Construction Set) based on a Microsoft Excel questionnaire was created in order to analyze and identify optimization potential in the development process of a company. This construction set was adapted to meet the requirements of the development department of a large Swiss insurance company in order to validate and test the framework with real data.

This case takes place at SCC, a recognized shopping mall located in Cali, Colombia. In March 2018, Javier Ortiz, CEO of SCC, contacted a group of researchers to identify the key success factors before the implementation of business intelligence practices. For this, the researcher's group conducted a set of deep semi-structured interviews to establish the current state of processes, people and technologies around business information. With this information, a business intelligence maturity stage model is presented to identify a low level of business intelligence practices, that represents a long list of challenges to be faced by the SCC with a limited budget. This case focuses on how to analyze the business intelligence readiness assessment using exploratory analysis, and seeks to promote the skills and competencies oriented to prioritize actions based on research to improve decision making before a business intelligence implementation project.

This study develops a Green Information Systems (IS) interpretive model grounded on Technology Organization Environment (TOE) framework to identify the factors that influence Green IS refraction and further examines to what extent these factors impact Green IS refraction in Information Communications Technology (ICT) based firms for corporate ecological responsibility reflection. For this purpose a survey was conducted among ICT based firms and analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM). Results indicate that the technological factors significantly influence Green IS refraction. In addition, results suggest that the organizational factors positively influence Green IS refraction. Moreover, results reveal that environmental factors significantly determine the extent of Green IS refraction. Finally, results show that Green IS reflection initiatives implemented in ICT based firms positively defines corporate ecological responsibility. Respectively, this study offers a comprehensive approach for measuring Green IS practice implemented in ICT based firms.

As one of the largest archipelagic countries in the world, Indonesia has been running the maritime highway system in recent years. This study focuses on how to improve the role of IOT platform in the maritime highway system. Furthermore, in this study, the authors are designing a new IOT system framework to support the operation of the maritime highway program in the seaport logistics system in archipelago countries, especially Indonesia. Each part of the port management stakeholders like port authority, commodity products company, shipping companies, and the government with their different policies (unique) in each island region has created its own IT system and links it to every website in its organization partially and not yet fully integrated. This research provides newly integrated frameworks with the IOT approach, and also a few recommendations related to practical and theoretical contributions that can be further developed in the seaports sector.

Artificial intelligence (AI) is changing the rules of the game in many industries. This case details how the combination of open innovation and artificial intelligence generates new opportunities in the tourism sector. Specifically, how to create new customer experiences through searching tools, social platforms and cognitive interfaces to make intelligent decisions. The authors show that it is possible to increase tourist satisfaction by offering a set of customized activities and experiences according to their personal characteristics and motivations. The combination of cutting-edge digital technologies makes it possible to design new services in an automated and cost-affordable manner. The experience has been carried out in Lanzarote (Canary Islands, Spain), with support of IBM's Watson system. This is a good example of AI-fueled innovation in services, which is adequate for courses on innovation, technology, entrepreneurship and competitive strategy.

Digital evidence has a different meaning from physical evidence, but even though it is different, both are a unity of evidence that supports each other in the investigation process. Unfortunately, laws and regulations generally have not been oriented to the terminology of digital evidence that should be. It becomes a research challenge in how the handling of digital evidence also gets the same treatment as physical evidence. For this reason, technical studies are needed to support the application of law and regulations for digital evidence handling. This article provides a solution in the form of digital evidence cabinets as a framework to support the centralization of digital evidence that following the applicable regulations of procedures for the management of evidence in the territory of Indonesia. This concept can translate the centralization of digital evidence through the analogy of physical cabinet and the interpretation of cabinet, rack, bags, and evidence unit with types of criminals, list of crimes, list of crime scenes and list of digital evidence at one crime scene.

Significant growth and successful integration of mobile devices to the education landscape have garnered the introduction of mobile learning (mLearning) as a new technology-enabled educational tool. Mobile learning has become a new higher educational paradigm which makes learning more flexible and accessible. However, student readiness and their perceptions about educational use of tablet devices are still a concern particularly in the developing countries like the Pacific island countries (PICs). This article investigates these two important attributes of tablet devices in a first year blended course from a higher education institute in the Pacific with a sample of 43 students.The results revealed that the participants perceived that tablet devices were effective and innovative learning tools. The participants supported the idea of using tablet devices and were ready to incorporate them for learning provided there was training in place. This article finally outlines recommendations for the education sectors in the Pacific.

In recent years, healthcare service providers have increasingly employed mobile systems in delivering services. However, the nature of the diversities in tribes and languages within many developing countries enhance the difficulty of delivering or receiving the services which are provided by many healthcare organisations. This is so because the English language is the primary medium of communication, although many healthcare recipients are not conversant in English as they cannot speak English fluently or understand it coherently. The objective of the study was to understand the impact which language barrier have on healthcare services. The interpretivist approach was employed. The case study approach was applied. Qualitative data were collected using semi-structured technique. The analysis of the data was guided by two theories, actor network theory and diffusion of innovation. From the findings, a framework was developed, which is intended to guide a solution that can be provided to address the barrier in the South African healthcare environment.

Open source software (OSS) has recently become very important due to the rapid expansion of the software industry. In order to determine whether the quality of the software can achieve the intended purposes, the components of OSS need to be assessed as they are in closed source (conventional) software. Several quality in-use models have been introduced to evaluate software quality in various fields. The banking sector is one of the most critical sectors, as it deals with highly sensitive data; it therefore requires an accurate and effective assessment of software quality. In this article, two pieces of banking software are compared: one open source and one closed source. A new quality in use model, inspired by ISO/IEC 25010, is used to ensure concise results in the comparison. The results obtained show the great potential of OSS, especially in the banking field.

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.

The aim of this paper is to demonstrate the intricacies of trust in an institutional setting with the help of a case entailing a clash between Apple and the FBI in a situation that was both politically and emotionally complex. The review of literature covers an extensive amount of academic papers to encapsulate each and every aspect of trust ranging from simple characterization of the concept to the deep-seated complexities of the matter like the effect of ethnicity on trust or the neurological effects during a breach of trust. Finally, it identifies serious gaps in research that are needed to be worked upon by other researchers to further our understanding of the matter.

Cloud computing has evolved as a new paradigm for management of an infrastructure and gained ample consideration in both industrial and academic area of research. A hidden Markov model (HMM) combined with Markov games can give a solution that may act as a countermeasure for many cyber security threats and malicious intrusions in a network or in a cloud. A HMM can be trained by using training sequences that may be obtained by analyzing the file traces of packet analyzer like Wireshark network analyzer. In this article, the authors have proposed a model in which HMM can be build using a set of training examples that are obtained by using a network analyzer (i.e., Wireshark). As it is not an intrusion detection system, the obtained file traces may be used as training examples to test a HMM model. It also predicts a probability value for each tested sequence and states if sequence is anomalous or not. A numerical example is also shown in this article that calculates the most optimal sequence of observations for both HMM and state sequence probabilities in case a HMM model is already given.