This paper presents the success story of the intuitive vision of an Information and Communication Technology (ICT) high school educator in South Africa. The growth and evolution of a Community of Practice towards a full-fledged living lab is investigated. A grounded theory study analyses the living lab concept and highlights some of the current challenges secondary high school ICT education face within the South African educational landscape. Some of the concepts, ideas, best practices, and lessons learned in the establishment and running of two web based technologies to support secondary school ICT subjects is discussed. The researchers present a motivation for the use of living labs to address some of the issues identified and highlights how the existing platforms fits into bigger design.

Aim/Purpose: The aim of this study was to develop a prototype of an information-generating computer tool designed to automatically map the dental restorations in a panoramic radiograph. Background: A panoramic radiograph is an external dental radiograph of the oro-maxillofacial region, obtained with minimal discomfort and significantly lower radiation dose compared to full mouth intra-oral radiographs or cone-beam computed tomography (CBCT) imaging. Currently, however, a radiologic informative report is not regularly designed for a panoramic radiograph, and the referring doctor needs to interpret the panoramic radiograph manually, according to his own judgment. Methodology: An algorithm, based on techniques of computer vision and machine learning, was developed to automatically detect and classify dental restorations in a panoramic radiograph, such as fillings, crowns, root canal treatments and implants. An experienced dentist evaluated 63 panoramic anonymized images and marked on them, manually, 316 various restorations. The images were automatically cropped to obtain a region of interest (ROI) containing only the upper and lower alveolar ridges. The algorithm automatically segmented the restorations using a local adaptive threshold. In order to improve detection of the dental restorations, morphological operations such as opening, closing and hole-filling were employed. Since each restoration is characterized by a unique shape and unique gray level distribution, 20 numerical features describing the contour and the texture were extracted in order to classify the restorations. Twenty-two different machine learning models were evaluated, using a cross-validation approach, to automatically classify the dental restorations into 9 categories. Contribution: The computer tool will provide automatic detection and classification of dental restorations, as an initial step toward automatic detection of oral pathologies in a panoramic radiograph. The use of this algorithm will aid in generating a radiologic report which includes all the information required to improve patient management and treatment outcome. Findings: The automatic cropping of the ROI in the panoramic radiographs, in order to include only the alveolar ridges, was successful in 97% of the cases. The developed algorithm for detection and classification of the dental restorations correctly detected 95% of the restorations. ‘Weighted k-NN’ was the machine-learning model that yielded the best classification rate of the dental restorations - 92%. Impact on Society: Information that will be extracted automatically from the panoramic image will provide a reliable, reproducible radiographic report, currently unavailable, which will assist the clinician as well as improve patients’ reliance on the diagnosis. Future Research: The algorithm for automatic detection and classification of dental restorations in panoramic imaging must be trained on a larger dataset to improve the results. This algorithm will then be used as a preliminary stage for automatically detecting incidental oral pathologies exhibited in the panoramic images.

Aim/Purpose: This work aims to understand why a disparity between the popularity of smart phones and the limited adoption of m-banking exists. Accordingly, this study investigates factors that affect a person’s decision to adopt m-banking services. Such an investigation seeks to determine if and to what extent customers’ mobile phone experience as well as their awareness of m-banking services influence their intention to use such services? Background: This study developed a conceptual model to determine the influence that users’ mobile phone experience as well as users’ awareness of m-banking services had on users’ behavioral intention to use m-banking in Saudi Arabia. Methodology: The quantitative method used to collect data was a survey questionnaire tech-nique. A questionnaire with non-structured (close-ended) questions was formulated. A random sample, targeting banking customers in Saudi Arabia, was selected. This study collected data using a cross-sectional survey. Of those surveyed, 389 provided valid responses eligible for data analysis. SPSS v.22 was used to analyze the data. Contribution: This study produced helpful results and a new m-banking conceptual model. The developed conceptual model focused integrally on users’ awareness and experience as antecedents of m-banking adoption and highlighted the im-portance of differentiating between measuring the users’ characteristics in adopting e-banking in general and m-banking services in particular. In addition, this type of model has the ability to synthesize new control variables as well as to study technology acceptance in developing countries. This study, based on an extended UTAUT model, set out to discover what factors might affect customers’ intentions to use m-banking in Saudi Arabia. Findings: The results show that service awareness has a direct effect on performance and effort expectancy, but not on perceived risk. Moreover, mobile phone experience fails to impact the relationships in the same hypothesized direction. As anticipated, performance expectancy, effort expectancy, and perceived risk have direct and significant effects on behavioral intentions to use m-banking. However, customer awareness fails to impact the relationships of performance expectancy, effort expectancy, and perceived risk on behavioral intentions to use m-banking. Recommendations for Practitioners: Banks should target customers by distributing useful information and applying measures to increase acceptance. Banks need to introduce something imaginative to convince bank customers to abandon existing service channels and adopt m-banking services. Banks should make m-banking services the easiest service for conducting bank transactions and/or help customers conduct transactions that they cannot do any other way. Recommendation for Researchers: Other factors, such as trust, culture, and/or credibility should be investigated along with user’s awareness and experience factors in m-banking services. There is a need to focus on a specific type of m-banking. Thus, it may be fruitful to study the adoption of different systems of m-banking services. Impact on Society: This study suggests that m-banking services should be designed and built based on a deep understanding of customers’ needs using extensive testing to assure that applications and sites function well in a mobile setting. Future Research: Future researchers should apply the conceptual model developed in this study in different settings, different countries, and to different technologies.

Aim/Purpose: In this paper, we present an RFM model-based telecom customer churn system for better predicting and analyzing customer churn. Background: In the highly competitive telecom industry, customer churn is an important research topic in customer relationship management (CRM) for telecom companies that want to improve customer retention. Many researchers focus on a telecom customer churn analysis system to find out the customer churn factors for improving prediction accuracy. Methodology: The telecom customer churn analysis system consists of three main parts: customer segmentation, churn prediction, and churn factor identification. To segment the original dataset, we use the RFM model and K-means algorithm with an elbow method. We then use RFM-based feature construction for customer churn prediction, and the XGBoost algorithm with SHAP method to obtain a feature importance ranking. We chose an open-source customer churn dataset that contains 7,043 instances and 21 features. Contribution: We present a novel system for churn analysis in telecom companies, which encompasses customer churn prediction, customer segmentation, and churn factor analysis to enhance business strategies and services. In this system, we leverage customer segmentation techniques for feature construction, which enables the new features to improve the model performance significantly. Our experiments demonstrate that the proposed system outperforms current advanced customer churn prediction methods in the same dataset, with a higher prediction accuracy. The results further demonstrate that this churn analysis system can help telecom companies mine customer value from the features in a dataset, identify the primary factors contributing to customer churn, and propose suitable solution strategies. Findings: Simulation results show that the K-means algorithm gets better results when the original dataset is divided into four groups, so the K value is selected as 4. The XGBoost algorithm achieves 79.3% and 81.05% accuracy on the original dataset and new data with RFM, respectively. Additionally, each cluster has a unique feature importance ranking, allowing for specialized strategies to be provided to each cluster. Overall, our system can help telecom companies implement effective CRM and marketing strategies to reduce customer churn. Recommendations for Practitioners: More accurate churn prediction reduces misjudgment of customer churn. The acquisition of customer churn factors makes the company more convenient to analyze the reasons for churn and formulate relevant conservation strategies. Recommendation for Researchers: The research achieves 81.05% accuracy for customer churn prediction with the Xgboost and RFM algorithms. We believe that more enhancements algorithms can be attempted for data preprocessing for better prediction. Impact on Society: This study proposes a more accurate and competitive customer churn system to help telecom companies conserve the local markets and reduce capital outflows. Future Research: The research is also applicable to other fields, such as education, banking, and so forth. We will make more new attempts based on this system.

Aim/Purpose: In this study, the research proposes and experiments with a new model of collecting, storing, and analyzing big data on customer feedback in the tourism industry. The research focused on the Vietnam market. Background: Big Data describes large databases that have been “silently” built by businesses, which include product information, customer information, customer feedback, etc. This information is valuable, and the volume increases rapidly over time, but businesses often pay little attention or store it discretely, not centrally, thereby wasting an extremely large resource and partly causing limitations for business analysis as well as data. Methodology: The study conducted an experiment by collecting customer feedback data in the field of tourism, especially tourism in Vietnam, from 2007 to 2022. After that, the research proceeded to store and mine latent topics based on the data collected using the Topic Model. The study applied cloud computing technology to build a collection and storage model to solve difficulties, including scalability, system stability, and system cost optimization, as well as ease of access to technology. Contribution: The research has four main contributions: (1) Building a model for Big Data collection, storage, and analysis; (2) Experimenting with the solution by collecting customer feedback data from huge platforms such as Booking.com, Agoda.com, and Phuot.vn based on cloud computing, focusing mainly on tourism Vietnam; (3) A Data Lake that stores customer feedback and discussion in the field of tourism was built, supporting researchers in the field of natural language processing; (4) Experimental research on the latent topic mining model from the collected Big Data based on the topic model. Findings: Experimental results show that the Data Lake has helped users easily extract information, thereby supporting administrators in making quick and timely decisions. Next, PySpark big data processing technology and cloud computing help speed up processing, save costs, and make model building easier when moving to SaaS. Finally, the topic model helps identify customer discussion trends and identify latent topics that customers are interested in so business owners have a better picture of their potential customers and business. Recommendations for Practitioners: Empirical results show that facilities are the factor that customers in the Vietnamese market complain about the most in the tourism/hospitality sector. This information also recommends that practitioners reduce their expectations about facilities because the overall level of physical facilities in the Vietnamese market is still weak and cannot be compared with other countries in the world. However, this is also information to support administrators in planning to upgrade facilities in the long term. Recommendation for Researchers: The value of Data Lake has been proven by research. The study also formed a model for big data collection, storage, and analysis. Researchers can use the same model for other fields or use the model and algorithm proposed by this study to collect and store big data in other platforms and areas. Impact on Society: Collecting, storing, and analyzing big data in the tourism sector helps government strategists to identify tourism trends and communication crises. Based on that information, government managers will be able to make decisions and strategies to develop regional tourism, propose price levels, and support innovative programs. That is the great social value that this research brings. Future Research: With each different platform or website, the study had to build a query scenario and choose a different technology approach, which limits the ability of the solution’s scalability to multiple platforms. Research will continue to build and standardize query scenarios and processing technologies to make scalability to other platforms easier.

Aim/Purpose: This study aimed to increase our understanding of how the stages of the customer purchase journey, privacy trade-offs, and information sensitivity of different business service sectors affect consumers’ privacy concerns. Background: The study investigated young consumers’ willingness to provide consent to use their personal data at different phases of the customer journey. This study also examined their readiness to provide consent if they receive personal benefits, and how information sensitivity varied between different individuals and business sectors. Methodology: Data was collected by a quantitative survey (n=309) and analyzed with R using the Bayesian linear mixed effect modeling approach. The sample consisted of university students in Finland, who represented a group of young and digitally native consumers. The questionnaire was designed for this study and included constructs with primarily Likert-scale items. Contribution: The study contributed to data privacy and consent management research in information sensitivity, privacy trade-off, and the customer journey. The study underlined the need for a stronger user experience focus and contextuality. Findings: The results showed that readiness to disclose personal data varied at different phases of the customer journey as privacy concerns did not decrease in a linear fashion throughout the purchase process. Perceived benefits affected the willingness to provide consent for data usage, but concerned consumers would be less trade-off oriented. Self-benefit was the most relevant reason for sharing, while customization was the least. There is a connection between the information sensitivity of different business sector information and privacy concerns. No support for gender differences was found, but age affected benefits and business sector variables. Recommendations for Practitioners: The study recommends approaching consumers’ data privacy concerns from a customer journey perspective while trying to motivate consumers to share their personal data with relevant perceived benefits. The self-benefit was the most relevant benefit for willingness to provide consent, while customization was the least. Recommendation for Researchers: The study shows that individual preference for privacy was a major factor directly and via interaction for all three models. This study also showed that consumers’ subjective decision-making in privacy issues is both a situational and a contextual factor. Impact on Society: This study could encourage policymakers and societies to develop guidelines on how to develop privacy practices and consent management to be more user centric as individuals are increasingly concerned about their online privacy. Future Research: This study encourages examining consumers’ motivational factors to provide digital consent for companies with experimental research settings. This study also calls to explore perceived benefits in all age groups from the perspective of different information in various business sectors. This study shows that privacy concern is a contextual and situational factor.

Aim/Purpose: Previous research has generally concentrated on identifying the variables that most significantly influence customer churn or has used customer segmentation to identify a subset of potential consumers, excluding its effects on forecast accuracy. Consequently, there are two primary research goals in this work. The initial goal was to examine the impact of customer segmentation on the accuracy of customer churn prediction in the banking sector using machine learning models. The second objective is to experiment, contrast, and assess which machine learning approaches are most effective in predicting customer churn. Background: This paper reviews the theoretical basis of customer churn, and customer segmentation, and suggests using supervised machine-learning techniques for customer attrition prediction. Methodology: In this study, we use different machine learning models such as k-means clustering to segment customers, k-nearest neighbors, logistic regression, decision tree, random forest, and support vector machine to apply to the dataset to predict customer churn. Contribution: The results demonstrate that the dataset performs well with the random forest model, with an accuracy of about 97%, and that, following customer segmentation, the mean accuracy of each model performed well, with logistic regression having the lowest accuracy (87.27%) and random forest having the best (97.25%). Findings: Customer segmentation does not have much impact on the precision of predictions. It is dependent on the dataset and the models we choose. Recommendations for Practitioners: The practitioners can apply the proposed solutions to build a predictive system or apply them in other fields such as education, tourism, marketing, and human resources. Recommendation for Researchers: The research paradigm is also applicable in other areas such as artificial intelligence, machine learning, and churn prediction. Impact on Society: Customer churn will cause the value flowing from customers to enterprises to decrease. If customer churn continues to occur, the enterprise will gradually lose its competitive advantage. Future Research: Build a real-time or near real-time application to provide close information to make good decisions. Furthermore, handle the imbalanced data using new techniques.

Aim/Purpose: This study investigates the factors that affect the repurchase intentions of Generation Z consumers in India’s online shopping industry, focusing on combining the Expectation-Confirmation Model (ECM) and Extended Technology Acceptance Model (E-TAM). The aim is to understand the intricate behaviors that shape technology adoption and sustained usage, which are essential for retaining customers in e-commerce. Background: Social media and other online platforms have significantly influenced daily life and become essential communication tools owing to technological advancements. Online shopping is no exception, offering a range of product choices, information, and convenience compared with traditional commerce. Indian retailers recognize this trend as an opportunity to promote their brands through e-shopping platforms, leading to increased competition. Generation Z comprises 32% of the world’s population and is a significant emerging customer base in India. Numerous studies have been conducted to study customers’ repurchase intention in the online shopping domain, but few studies have explicitly focused on Generation Z as a customer base. This study aims to comprehensively understand the topic and investigate the variables that impact consumers’ online repurchase intention by examining their post-adoption behavioral processes. Methodology: The study employed a quantitative research design with structural equation modeling using AMOS to analyze responses from 410 participants. This method thoroughly examined hypotheses regarding factors affecting repurchase intention (security, ease of use, privacy, and internet self-efficacy) and the mediating role of e-satisfaction. Contribution: This study makes a unique contribution to the field of e-commerce by focusing on Generation Z in India, a rapidly growing demographic in the e-commerce industry. The results on the mediating role of e-satisfaction have significant implications for e-retailers seeking to enhance customer retention strategies and gain a competitive edge in the market. Findings: The research findings underscore the significant influence of security, ease of use, and internet self-efficacy on repurchase intentions, with e-satisfaction playing a pivotal role as a mediating factor. Notably, while privacy concerns did not directly impact repurchase intentions, they displayed considerable influence when mediated by e-satisfaction, highlighting the intricate interplay between these variables in the context of online shopping, which is the unique finding of this study. Recommendations for Practitioners: This study has several significant implications for practitioners. Effectively addressing computer-related individual differences, such as computer self-efficacy, is crucial for boosting online customers’ repurchase intention. For instance, if an e-retailer intends to target Generation Z customers, they should collaborate with IT professionals and develop various computer literacy programs on online streaming platforms, such as YouTube. These programs will enhance target customers’ confidence in online shopping portals and increase their online repeat purchases. Additionally, practitioners should strive to improve the online shopping experience by making the portal user-friendly. Generation Z is accustomed to a fast Internet experience, so they prefer that the process of completing online transactions is swift with fewer clicks. The search for products, payments, and redress should not be tedious. Furthermore, the primary objective of the e-retailer should be to satisfy customers, as satisfied customers repeat their purchases and increase overall profitability. Recommendation for Researchers: The current study was conducted in the Delhi-NCR region of India, and its findings could serve as a basis for future research. For instance, the scale devised in this study could be utilized to examine the impact of cash-on-delivery as a payment method on purchase intention across the country. Alternatively, a comparative analysis could be conducted to compare cash-on-delivery effects in various countries. Impact on Society: The study’s findings enable stakeholders in the online shopping industry to comprehend the post-adoption behavior of Generation Z users and augment existing literature by establishing a correlation between determinants that impact repurchase intention and e-satisfaction, which serves as a mediator. Future Research: This study examines the factors that impact the propensity of Generation Z shoppers to engage in repeat online purchases. This study focuses on India, where the Generation Y (millennial) customer base is also substantial within the online shopping market. Future research could compare the shopping habits of Generation Z and Generation Y customers, as the latter may place greater importance on privacy and security. Additional studies could broaden the scope of this research and explore the comparative viewpoints of both generations. Also, it would be advantageous to conduct in-depth interviews and longitudinal studies to acquire a more in-depth comprehension of the evolving digitalization of shopping.

Aim/Purpose: This study investigates the relationship between Electronic Word-of-Mouth (EWOM), Information Adoption, and the stock investment of Vietnamese investors. Background: Misinformation spreads online, and a lack of strong information analysis skills can lead Vietnamese investors to make poor stock choices. By understanding how online conversations and information processing influence investment decisions, this research can help investors avoid these pitfalls. Methodology: This study applies Structural Equation Modelling (SEM) to investigate how non-professional investors react to online information and which information factors influence their investment decisions. The final sample includes 512 investors from 18 to 65 years old from various professional backgrounds (including finance, technology, education, etc.). We conducted a combined online and offline survey using a convenience sampling method from August to November 2023. Contribution: This study contributes to the growing literature on Electronic Word-of-Mouth (EWOM) and its impact on investment decisions. While prior research has explored EWOM in various contexts, we focus on Vietnamese investors, which can offer valuable insights into its role within a developing nation’s stock market. Investors, particularly those who are new or less experienced, are often susceptible to the influence of EWOM. By examining EWOM’s influence in Vietnam, this study sheds light on a crucial factor impacting investment behavior in this emerging market. Findings: The results show that EWOM has a moderate impact on the Information Adoption and investment decisions of Vietnamese stock investors. Information Quality (QL) is the factor that has the strongest impact on Information Adoption (IA), followed by Information Credibility (IC) and Attitude Towards Information (AT). Needs for Information (NI) only have a small impact on Information Adoption (IA). Finally, Information Adoption (IA) has a limited influence on investor decisions in stock investment. We also find that investors need to verify information through official sites before making investment decisions based on posts in social media groups. Recommendations for Practitioners: The findings suggest that state management and media agencies need to coordinate to improve the quality of EWOM information to protect investors and promote the healthy development of the stock market. Social media platform managers need to moderate content, remove false information, prioritize displaying authentic information, cooperate with experts, provide complete information, and personalize the experience to enhance investor trust and positive attitude. Securities companies need to provide complete, accurate, and updated information about the market and investment products. They can enhance investor trust and positive attitude by developing news channels, interacting with investors, and providing auxiliary services. Listed companies need to take the initiative to improve the quality of information disclosure and ensure clarity, comprehensibility, and regular updates. Use diverse communication channels and improve corporate governance capacity to increase investor trust and positive attitude. Investors need to seek information from reliable sources, compare information from multiple sources, and carefully check the source and author of the information. They should improve their investment knowledge and skills, consult experts, define investment goals, and build a suitable investment portfolio. Recommendation for Researchers: This study synthesized previous research on EWOM, but there is still a gap in the field of securities because each nation has its laws, regulations, and policies. The relationships between the factors in the model are not yet clear, and there is a need to develop a model with more interactive factors. The research results need to be further verified, and more research can be conducted on the influence of investor psychology, investment experience, etc. Impact on Society: This study finds that online word-of-mouth (EWOM) can influence Vietnamese investors’ stock decisions, but information quality is more important. Policymakers should regulate EWOM accuracy, fund managers should use social media to reach investors, and investors should diversify their information sources. Future Research: This study focuses solely on the stock market, while individual investors in Vietnam may engage in various other investment forms such as gold, real estate, or cryptocurrencies. Therefore, future research could expand the scope to include other investment types to gain a more comprehensive understanding of how individual investors in Vietnam utilize electronic word-of-mouth (EWOM) and adopt information in their investment decision-making process. Furthermore, while these findings may apply to other emerging markets with similar levels of financial literacy as Vietnam, they may not fully extend to countries with higher financial literacy rates. Hence, further studies could be conducted in developed countries to examine the generalizability of these findings. Finally, future research could see how EWOM’s impact changes over a longer period. Additionally, a more nuanced understanding of the information adoption process could be achieved by developing a research model with additional factors.

Aim/Purpose: This study focuses on two targeting strategies of out-store Location-Based Mobile Advertising (LBMA): the geo-fencing strategy (i.e., targeting customers who are near the focal store) and the geo-conquesting strategy (i.e., targeting those who are near competitors’ stores to visit the focal store). To the authors’ knowledge, no previous studies have compared the perceived intrusiveness of advertisements (ads) in geo-fencing and geo-conquesting settings, despite the accumulating literature on out-store LBMA. Hence, the aim of this study is to determine which targeting strategy is more effective in terms of reducing the perception of ads’ intrusiveness and increasing positive customers’ attitudes and purchase intention. Background: The intrusive nature of LBMA is perceived negatively by some customers, impacting their attitudes toward the ad, purchase intention, and even their perception of the brand. Therefore, identifying the targeting strategy under which ads are perceived as less intrusive is essential. Additionally, brick-and-mortar clothing stores in Jordan are facing challenges due to the rise of online shopping and increased competition from nearby stores. Thus, examining geo-fencing and geo-conquesting might tackle these challenges and encourage local clothing retailers to adopt these strategies. Methodology: A quantitative method was used in this study. A between-subjects experimental design was used to collect the data using a scenario-based survey distributed to Jordanians aged 18 to 45. A total of 531 responses were collected. After excluding those who do not belong to the targeted age group and those who did not pass the manipulation check, 406 responses were analyzed using the Statistical Package for the Social Sciences (SPSS) software version 28 and the Analysis of Moment Structures (AMOS) software version 26 to conduct Structural Equation Modeling (SEM). Contribution: This work offers valuable contributions by investigating the impact of the perceived intrusiveness of ads on purchase intention in the contexts of geo-fencing and geo-conquesting, which has not been studied before. Additionally, it fills a gap by examining this phenomenon in Jordan, a developing country in which attitudes toward LBMA have not been previously explored. Findings: The results revealed that location-based mobile ads sent under a geo-fencing strategy are perceived as less intrusive than those sent under a geo-conquesting strategy. In addition, customers’ attitudes fully mediate the relationship between intrusiveness and purchase intention only under the geo-fencing strategy. Ultimately, neither of the strategies is more effective in terms of increasing positive customer attitudes and purchase intentions in the context of clothing retail stores in Jordan. Recommendations for Practitioners: Clothing retailers in Jordan should consider adopting geo-fencing and geo-conquesting strategies to boost purchase intentions and tackle industry challenges. Additionally, to increase purchase intentions with geo-fencing, practitioners should focus on fostering positive customer attitudes toward ads, as simply perceiving them as less intrusive is not sufficient to drive purchase intention without the mediating effect of positive attitudes. Recommendation for Researchers: This research is crucial for academics and researchers as geolocation technology and LBMA are expected to advance significantly in the future. Researchers can investigate this topic through a randomized field experiment, followed by a research questionnaire to collect data from a real-world setting. Impact on Society: Utilizing LBMA is essential for local clothing retail stores that are trying to effectively reach and connect with their customers because searching the Internet for local goods and services is done primarily on mobile devices. Indeed, this study revealed that customers in both settings (i.e., geo-fencing and geo-conquesting) reported a high intention to visit the promoting store and to purchase from the advertised product category. Future Research: Future research can apply this topic to different industries and cultural contexts, as the results may vary across industries and regions. Moreover, future research could build on this study by investigating additional constructs, such as product category involvement, customization, and content type of the message (e.g., informative, entertaining).

Unmanned stores are one of the latest conceptual developments in retail and have received much attention, especially in the context of COVID-19-related social restrictions and the associated changes in consumer behaviour. The concept considers the latest technological developments and promises to offer various benefits to consumers and retailers based on artificial intelligence and automation. Using a German sample, this paper aims to evaluate consumers' acceptance of and intention to use the most prominent innovative solutions in unmanned stores. A modified technology acceptance model (TAM) as a theoretical framework was applied to the study. The results of the structural equation modelling make two contributions to the existing literature: First, the acceptance criteria for unmanned stores have not been analysed previously. Second, the modified TAM could be confirmed in this study. We provide empirical evidence suggesting that significant numbers of consumers accept unmanned stores, especially if the stores are strategically located and when individuals have a high innovation affinity.

Aim/Purpose: The teaching solution presented in this paper was implemented to overcome the common problems encountered by authors during years of practice of applied business studies teaching. Background: In our school, we have deep multicultural environments where both teachers and students are coming from different countries and cultures. The typical problems encountered with students include: not reading the case studies, language problems, different backgrounds and cultures, a different understanding of leadership in teamwork related to various management traditions, lack of student participation, and engagement in teamwork. Methodology : The above problems were solved on the basis of the novelty use of several tools usually used separately: a combination of case studies with visualization and current representation of knowledge related to the case study. The visualization context is provided by “rich picture” (as a part of SSM methodology) to create a shared understanding among students. Another ingredient of the proposed solution is based on Pacific storytelling tradition and the Pacific methodology of solving problems. Contribution: It was suggested the new delivery model strengthening advantages of case studies. Findings: Studies and surveys made from 2009 to the present are promising. There is a visible improvement in students’ grades and observed changes in students’ behavior toward more active in-class participation. Recommendations for Practitioners: This paper focuses on implementation and technical aspects of the presented method. However, the application of the presented method needs robust and time-consuming preparation of the teacher before the class. Recommendation for Researchers: The current results show that the proposed method has the potential to improve students’ experience in applied business courses. The project is ongoing and will undergo progressive changes while collecting new experiences. The method may be applied to other types of courses. By focusing on the storytelling and rich picture, we avoid technological bias when we teach business problem-solving. We focus instead on teaching students the social-organizational interactions influencing the problem solution. Impact on Society: Implementing of cultural sensitivity into the teaching process. Making teaching process more attractive for multicultural students. Future Research: Reducing teacher overload when using the method presented by the development of computerized tools. This is undergoing through utilizing Unreal Engine. Also, it is planned to enhance our team by artists and designers related to computer games.

This paper discusses applications of the measures of the risk of misinforming and the role of the warranty of misinforming in the context of the informing component of Customer Related Management (CRM) issues. This study consists of two parts. Firstly, we propose an approach for customers’ grouping based on their attitude toward assessing product's properties and their expertise on the terminology/domain of the seller’s message describing the product. Also we discuss what the most appropriate personal/group warranty is for each of these group/clusters. 

Myung-Hyun KIM,Seungkwang LEE, Vol.E107-D, No.11, pp.1449-1452
White-box cryptographic implementations often use masking and shuffling as countermeasures against key extraction attacks. To counter these defenses, higher-order Differential Computation Analysis (HO-DCA) and its variants have been developed. These methods aim to breach these countermeasures without needing reverse engineering. However, these non-invasive attacks are expensive and can be thwarted by updating the masking and shuffling techniques. This paper introduces a simple binary injection attack, aptly named clear & return, designed to bypass advanced masking and shuffling defenses employed in white-box cryptography. The attack involves injecting a small amount of assembly code, which effectively disables run-time random sources. This loss of randomness exposes the unprotected lookup value within white-box implementations, making them vulnerable to simple statistical analysis. In experiments targeting open-source white-box cryptographic implementations, the attack strategy of hijacking entries in the Global Offset Table (GOT) or function calls shows effectiveness in circumventing run-time countermeasures.
Publication Date: 2024/11/01

Naoya NEZU,Hiroshi YAMADA, Vol.E107-D, No.11, pp.1408-1421
Modern memory devices such as DRAM are prone to errors that occur because of unintended bit flips during their operation. Since memory errors severely impact in-memory key-value stores (KVSes), software mechanisms for hardening them against memory errors are being explored. However, it is hard to efficiently test the memory error handling code due to its characteristics: the code is event-driven, the handlers depend on the memory object, and in-memory KVSes manage various objects in huge memory space. This paper presents MemFI that supports runtime tests for the memory error handlers of in-memory KVSes. Our approach performs the software fault injection of memory errors at the memory object level to trigger the target handler while smoothly carrying out tests on the same running state. To show the effectiveness of MemFI, we integrate error handling mechanisms into a real-world in-memory KVS, memcached 1.6.9 and Redis 6.2.7, and check their behavior using the MemFI prototypes. The results show that the MemFI-based runtime test allows us to check the behavior of the error handling mechanisms. We also show its efficiency by comparing it to other fault injection approaches based on a trial model.
Publication Date: 2024/11/01

Calls for greater diversity in management research, education and practice have increased in recent years, driven by a sense of fairness and ethical responsibility, but also because research shows that greater diversity of inputs into management processes can lead to greater innovation. But how can greater diversity of thought be encouraged when educating management students, beyond the advocacy of affirmative action and relating the research on the link between multiplicity and creativity? One way is to think again about how we introduce the subject. Introductory textbooks often begin by relaying the history of management. What is presented is a very limited mono-cultural and linear view of how management emerged. This article highlights the limits this view outlines for initiates in contrast to the histories of other comparable fields (medicine and architecture), and discusses how a wider, deeper and more engaged understanding of history can foster thinking differently.

The interview questions deal with the means by which Estonia and other republics of the former Soviet Union managed to transform their educational systems and the impact of the Soviet heritage on this transformation. An interview was conducted with Professor Olav Aarna. In 1991 Professor Olav Aarna became the rector of TUT. From 2000 to 2003 he held the position of rector of the first private university in Estonia - Estonian Business School (EBS). From 2003 to 2007 Olav Aarna was member of the Estonian Parliament, serving also as Chairman of the Committee for Cultural Affairs responsible for education, research, culture and sports affairs. From 1998-2000 he was Vice Chairman of Estonian National Council for Research and Development. His experience in the field of educational legislation stems from his advisory position to the Minister of Education of Estonia from 1990 to1992. His competence in the field of the Bologna process results from the development of higher education legislation in Estonia (2002-...) and the development of a higher education quality assurance system for Estonia (2008-...). Olav Aarna has consulted third countries in the national qualifications framework (NQF) development as a European Training Foundation (ETF) expert.

Prior research on mergers and acquisitions (M&As) has substantially advanced our understanding of how isolated acquirer- and deal-specific factors affect abnormal returns. However, investors are likely to perceive and evaluate M&As holistically—that is, as complex configurations (i.e., Gestalts) of characteristics, rather than as a list of independent factors. Yet, extant M&A literature has not addressed why and how configurations of factors elicit positive or negative reactions. In other words, overlooking the interdependent nature of factors known to influence acquisition success has limited our understanding of both M&As and investor judgment. Taking an inductive approach to addressing this important issue, this study relies on fuzzy set methodology. Our results provide compelling evidence that investor perceptions of M&A announcements are not only configurational in nature but also characterized by equifinality - or the presence of multiple paths to success - and asymmetric causality - that is, configurations that represent bad deals are not simply a mirror image of good deals, but differ fundamentally. By constructing a typology of "good" and "bad" deals as perceived by market participants, we develop a mid-range theory of M&A stock market performance. As such, this study offers novel theoretical and empirical insights to scholars, and implications for practitioners.

The promise of a closer union between organizational and historical research has long been recognized. However its potential remains unfulfilled: the authenticity of theory development expected by organization studies and the authenticity of historical veracity required by historical research place exceptional conceptual and empirical demands on researchers. We elaborate the idea of historical organization studies, organizational research that draws extensively on historical data, methods and knowledge to promote historically informed theoretical narratives attentive to both disciplines. Building on prior research, we propose a typology of four differing conceptions of history in organizational research: history as evaluating, explicating, conceptualizing, and narrating. We identify five principles of historical organization studies - dual integrity, pluralistic understanding, representational truth, context sensitivity and theoretical fluency - and illustrate our typology holistically from the perspective of institutional entrepreneurship. We explore practical avenues for a creative synthesis, drawing examples from social movement research and micro-history. Historically informed theoretical narratives whose validity derives from both historical veracity and conceptual rigor, afford dual integrity that enhances scholarly legitimacy, enriching understanding of historical, contemporary and future-directed social realities.

We examine how top management team (TMT) misfit, defined as discrepancies between the TMT's functional roles and the qualifications of the managers who fill those roles, affects the evolution of TMT composition and structure in a longitudinal study of entrepreneurial ventures. We distinguish two types of misfit - overqualification and underqualification - and study how each is associated with TMT changes. We further consider the moderating effect of firm development. Results reveal that underqualified TMTs hire new managers to reinforce existing capabilities whereas overqualified TMTs elaborate their role structures. However, achieving developmental milestones (i.e., obtaining venture capital funding and staging an initial public offering) is a critical contingency to TMT change: absent these milestones, firms neither hire new managers nor add roles, even when they seemingly need to do so. These findings contribute to knowledge of how TMTs and new ventures evolve by underscoring the importance of simultaneously attending to TMT composition and structure.

We draw on the historiographical concepts of "generational units" and "collective memories" as a framework for understanding the emergence of entrepreneurially oriented cohesive groups within regions. Generational units are localized subgroups within generations that have a self-referential, reflexive quality, by virtue of the members' sense of their own connections to each other and the events that define them. Collective memories are shared accounts of the past shaped by historical events that mold individuals' perceptions. The two concepts provide a valuable point of departure for incorporating historical concepts into the study of entrepreneurial dynamics and offer a framework for understanding how entrepreneurs' historically situated experiences affect them. Our framework breaks new theoretical ground in several ways. First, we synthesize disparate literatures on generational units, collective memory, and organizational imprinting. Second, we specify mechanisms through which imprinting occurs and persists over time. We develop analytical arguments framed by sociological and historiographical theories, focusing on the conditions under which meaningful generational units of entrepreneurs may emerge and benefit from leadership and legacy building, technologies of memory, and institutional support that increases the likelihood of their persistence.

Despite the proliferation of strategy process and practice research, we lack understanding of the historical embeddedness of strategic processes and practices. In this paper, we present three historical approaches with the potential to remedy this deficiency. First, realist history can contribute to a better understanding of the historical embeddedness of strategic processes; in particular, comparative historical analysis can explicate the historical conditions, mechanisms, and causality in strategic processes. Second, interpretative history can add to our knowledge of the historical embeddedness of strategic practices, and microhistory can specifically help to understand the construction and enactment of these practices in historical contexts. Third, poststructuralist history can elucidate the historical embeddedness of strategic discourses, and genealogy can in particular increase our understanding of the evolution and transformation of strategic discourses and their power effects. Thus, this paper demonstrates how in their specific ways historical approaches and methods can add to our understanding of different forms and variations of strategic processes and practices, the historical construction of organizational strategies, and historically constituted strategic agency.

This study draws on social identity theories of behavioral contagion and research concerning narratives in organizations to present and test a framework for understanding how narratives embed values in organizational newcomers' actions. Employing a field experiment using 632 newly-hired employees in a large IT firm that prioritizes self-transcendent values, this study explores how narratives varying in terms of the organizational level of main characters and the values-upholding or values-violating behaviors of those characters influence newcomers' tendencies to engage in behaviors that uphold or deviate from the values. Results indicate that stories about low-level organizational characters engaging in values-upholding behaviors are more positively associated with self-transcendent, helping behaviors and negatively associated with deviant behaviors, than are similar stories about high-level members of the organization. Stories in which high-level members of the organization violate values are negatively related to newcomers' engagement in both helping and deviance more strongly than are values-violating stories about lower-level members. Content analyses of the stories suggest that they convey values in different and potentially important ways. Implications, future directions, and limitations are discussed.

It has accused X of promoting "disturbing content", and says Mr Musk is using it to "shape political discourse."

A new Trump administration will be far better prepared to restore Constitutional order than the first Trump administration.

Plano Field Ammo Box Heavy-Duty Storage Case - $6.99  each with FREE returns and FREE shipping for order over $35.00.

Archon Firearms and the Type B are far from the typical company or product and it shows. Video tabletop and shooting impressions review.

RTAC Large Lasercut MOLLE Backpack with a Pistol Retention System is not just $20.99 after a sale and coupon code at check out. That is 75%+ off...

Merica! Celebrate the landslide trump election win with a limited edition GLOCK 19 Gen 3 "Trump 2024 Mug Shot" 9mm Pistol, now at just $569.99.

BUILDINGS contribute 80-90% of the world’s carbon emission; they thus represent the biggest opportunities for climate-change mitigation through carbon reduction.

Universities, as owners of buildings that remain theirs for years to come, have a special responsibility to arrest climate change through sustainable operation. Management and Science University (MSU) recently achieved a Diamond-2 rating in the SEDA Malaysia Sustainable Energy Low Carbon Building Assessment 2020.

Recording 24.21% less emission against baseline measurements in 2019 – an annual saving of 5,646,661 kWh or 3,918.78 tonnes less carbon dioxide in 2020 – MSU is well on its way to supporting governmental target of 40-45% less CO2 in 2030.

In honour of this achievement, MSU President Professor Tan Sri Dato’ Wira Dr Mohd Shukri Ab Yajid was presented with the University’s first green certification by SEDA Acting Chief Strategic Officer TS Steve Anthony Lojuntin.

With the Green Pass, MSU emerged the first private institution of higher education in Malaysia to receive the Sustainable Energy Development Authority (SEDA) Diamond-2 rating.

OUR nation’s foundation is built on multiculturalism, which sets Malaysia apart from other countries in the world. We stand out because we have demonstrated to the world how people of all races, religions and cultures can live together in harmony.

There is no place for racism or sexism in this beautiful nation of ours, and all forms to spread any of these must be rejected.

However, two recent allegations highlighted by the National Union of Bank Employees (NUBE) are deeply disturbing and pose a threat to the values our proud nation has fought for – that all Malaysians are equal.

It disturbs me that in this day and age, there are still those who resort to racism and sink so low as to call a fellow worker “black”.

It is demeaning to label a person as “black” just because of the person’s skin colour, and such a horrid act should not go unpunished.

As a fellow Malaysian, regardless of religion, I am appalled by such an act and call upon our unity minister to look into this matter and put an end to such practices.

It is our unity that has brought us this far, and now it is time to weed out those who still practise racism and eliminate this culture.

Another reported incident recently highlighted by NUBE involved a woman who was allegedly sexually harassed and bullied, only to be abruptly dismissed a day before Deepavali.

The bank’s excuse that she was dismissed for failing to attend an internal inquiry is utterly pathetic.

Instead, the bank should have offered the victim support and counselling after she endured years of sexual harassment.

According to reports, it is alleged that the perpetrator demanded she sleep with him and even sent her lewd pictures of himself.

Is the bank condoning sexual discrimination? The minister responsible must take immediate action to put an end to such harassment.

Sexual harassment cases must not go unchecked, as they remain a significant issue for many. According to the All Women’s Action Society, such cases are on the rise.

If these cases are reported but go unpunished, it will embolden more perpetrators to become increasingly daring in victimising women.

The two alleged incidents are deeply shocking and should be unequivocally condemned by our society. The relevant ministers and authorities must not turn a blind eye to this issue and must take immediate action to put an end to such practices.

Sarah Ibrahim Daud

Shah Alam

KUALA LUMPUR: Bursa Malaysia Bhd is experiencing a resurgence in IPOs as 2024 draws to a close, reflecting renewed investor confidence in the local bourse.

With 44 initial public offerings to date, Bursa Malaysia has outpaced other markets in Southeast Asia, emerging as an attractive IPO destination amid a stable economic and political landscape.

According to Mohd Sedek Jantan, UOB Kay Hian Wealth Advisors’ head of investment research, several factors have contributed to this surge. “The risk of doing business in the fourth quarter has subsided as major economic and political uncertainties have passed, such as the US presidential election while Malaysia’s active role in international forums has bolstered the country’s global standing,” he told Bernama.

He reckons that Malaysia’s stable economic indicators, including positive trade figures, healthy employment rates and steady industrial production have fostered a predictable business environment that encourages IPO activity. “Political stability and a clear government policy framework further enhance investor confidence,” he said.

The surge in IPOs on Bursa Malaysia underscores the local bourse’s resilience compared to other regional markets.

Mohd Sedek noted that Malaysia has recorded 36 IPOs so far this year, raising about US$450 million in the first half alone, which accounts for 33% of Southeast Asia’s total IPO proceeds.

“This stands in contrast to a subdued IPO market across the Asia-Pacific, where proceeds have dropped by 63%, largely due to challenges in China and Hong Kong.

“Malaysia has outperformed both Indonesia and Singapore in IPO activity this year,” he pointed out, highlighting that Indonesia faces political uncertainty following its recent presidential election, while Singapore has seen a slowdown in activity due to high regulatory costs and weak investor demand.

In contrast, he said Malaysia’s IPO market benefits from a stable macroeconomic backdrop, business-friendly regulations, and the supportive Madani Economy Framework.

Mohd Sedek said the growth in IPOs reflects optimism in key Malaysian sectors, with recent listings from the construction, manufacturing, and healthcare industries.

He said in the construction sector, which expanded by 22.9% in the third quarter, private and public investments in residential, non-residential, and large-scale infrastructure projects are expected to drive further growth. “Key government initiatives, such as RM9 billion for private finance initiatives and RM25.5 billion from government-linked investment companies are expected to sustain this momentum,” he added.

In the manufacturing sector, Malaysia’s transformation under the New Industrial Master Plan 2030 aims to drive growth in high-value, technology-driven industries. “The government’s focus on digitalisation, green technology, and advanced manufacturing techniques is expected to attract further investments, solidifying Malaysia’s position as a competitive manufacturing hub in Asean,” he said.

Malaysia’s healthcare sector is also expanding due to demographic shifts and rising health awareness. The integration of technology, such as telemedicine and digital health solutions, is anticipated to boost the sector’s growth by improving care accessibility and efficiency. “This trend, coupled with government support for medical tourism, positions Malaysia as a key player in the healthcare industry in the region,” Mohd Sedek said.

Bursa Malaysia CEO Datuk Muhamad Umar Swift expressed satisfaction with the IPO momentum, noting that three Main Market IPOs were listed this week alone.

“This surge reflects a thriving capital market with strong regulatory support and a diverse investor pool. Malaysia has experienced a bull run, making us the Asean exchange with the highest number of IPOs to date this year,” he said.

Echoing this sentiment, the exchange regulator’s chairman Tan Sri Abdul Wahid Omar highlighted the significance of Monday’s listings, which took place on the auspicious date of 11.11. (Nov 11)

“Both companies chose that date for its auspicious nature, marking a rare occasion of two listings on the same day. The last time Bursa hosted two listings on a single day was in November 2017, following the demerger of Sime Darby Group, which saw both Sime Darby Plantation Bhd and Sime Darby Property Bhd debut together,” he said.

Bank Muamalat Malaysia Bhd chief economist Dr Mohd Afzanizam Abdul Rashid noted that the strong IPO pipeline signals positive prospects for the Malaysian economy, as stable policies and a clear path towards becoming a high-income nation attract investor interest.

“Malaysia’s equities are undervalued, offering upside potential. The economic and policy stability enhances investor confidence, while companies’ growth trajectories inspire optimism for the market’s future,” he said.

Mohd Afzanizam said that as Bursa Malaysia continues to attract IPOs, he expects the exchange’s momentum to inspire small and medium enterprises to pursue similar growth opportunities. “The record-setting IPO activity underscores Malaysia’s resilience and strong capital market position in Asean, providing a positive outlook for 2025,” he added. – Bernama

It is often said that China is the world’s foremost peddler of fake news and distorted truths. The recent incident in the Taiwan Strait exemplifies this assertion.

Celebrity couple Tom Holland and Zendaya are the highlight names in the cast for Academy Award-winning director Christopher Nolan's next movie.

...

...

...

...

If you're fed up with coming home to a mailbox full junk mail, you should know that there are some things you can do to stop it.

The post 4 Ways To Stop Junk Mail appeared first on Clark Howard.