Aim/Purpose: Most research on work-based learning and research relates to theory, including perspectives, principles and curricula, but few studies provide contemporary examples of work-based projects, particularly in the Australian context; this paper aims to address that limitation. Background: The Professional Studies Program at University of Southern Queensland is dedicated to offering advanced practice professionals the opportunity to self-direct organizational and work-based research projects to solve real-world workplace problems; two such examples in the Australian context are provided by this paper. Methodology: The paper employs a descriptive approach to analyzing these two work-based research projects and describes the mixed methods used by each researcher. Contribution: The paper provides examples of work-based research in (a) health, safety, and wellness leadership and its relation to corporate performance; and (b) investigator identity in the Australian Public Service; neither topic has been examined before in Australia and little, if anything, is empirically known about these topics internationally. Findings: The paper presents the expected outcomes for each project, including discussion of the ‘triple dividend’ of personal, organizational, and practice domain benefits; as importantly, the paper presents statements of workplace problems, needs and opportunities, status of the practice domain, background and prior learning of the researchers, learning objectives, work-based research in the practice domain, and lessons learned from research which can be integrated into a structured framework of advanced practice. Recommendations for Practitioners: This is a preliminary study of two work-based research projects in Australia; as these and other real-world projects are completed, further systematic and rigorous reports to the international educational community will reveal the granulated value of conducting projects designed to change organisations and concordant practice domains. Recommendation for Researchers: While introducing the basic elements of research methods and expected out-comes of work-based projects, examples in this paper give only a glimpse into the possible longer-term contributions such research can make to workplaces in Australia. Researchers, as a consequence, need to better understand the relationship between practice domains, research as a valuable investigative tool in workplaces, and organizational and social outcomes. Impact on Society: Work-based learning and research have been developed to not only meet the complex and changing demands of the global workforce but have been implemented to address real-world organizational problems for the benefit of society; this paper provides two examples where such benefit may occur. Future Research: Future research should focus on the investigation of triple-dividend outcomes and whether they are sustainable over the longer term.

Aim/Purpose: Work-based learning has been identified in the literature, and is established in academia and in the global worlds of work; however, an examination of work-based research, particularly at the doctoral level, has been less well articulated. Moreover, a paucity of published literature on either work-based research or Professional Studies means little is known about the dynamics and drivers of these domains. This study aims to begin addressing the shortfall in literature on work-based research and Professional Studies programs, using the program at University of Southern Queensland as an example Background: This paper examines work-based research in the context of the Professional Studies program at University of Southern Queensland in Australia, with which the authors are affiliated. Methodology: Analysis of work-based research includes discussion of ‘messy’ research environments and the changing nature of workplaces, along with the opportunities and challenges such environments pose for action researchers. Contribution: In addition to addressing a shortfall in the published literature on work-based research, the paper also contributes insight into the mechanisms used to promote reflective practice and the generation of professional artefacts. Findings: Often driven by altruism, work-based research as implemented in the Professional Studies program results in a so-called ‘triple dividend’, designed to benefit the individual researcher, work environment, and community of practice. Recommendations for Practitioners: To be successful contributors to work-based research, practitioners need to reflect carefully and deeply on experience, planning and outcomes, using what in this paper we call ‘micro-reflective’ (personal) and ‘macro-reflective’ (program) cycles of reflection. Recommendation for Researchers: In addition to generating new knowledge and expanding the frontiers of workplaces, work-based research is often motivated by complicated and wide-reaching imperatives; work-based researchers therefore need to consider the goals, objectives, priorities and vision of their work environments, as well as understand issues related to bias, ethical practice and the nature of insider research. Impact on Society: Work-based learning and research address the complexities, challenges and future demands of Australian workplaces along with the work, mobility and personal development needs of mid- to senior-career professionals. Future Research: In addition to the multitude of action research programs possible in work-places in Australia, more research is needed to understand higher education work-based learning and its relation to, and impact on, work-based research, particularly when applying mixed methods research to work environments.

Aim/Purpose: This article aimed to design and evaluate a pedagogical technique for altering students’ classroom digital multitasking behaviors. The technique we designed and evaluated is called course-based undergraduate research experience (CURE). With this technique, the students wrote a research article based on a multitasking experiment that the instructor conducted with the students. The students conducted a literature review, developed their own research questions, they analyzed experiment data, and presented results. This study evaluated the how the CURE contributed to student multitasking behavior change. Background: Multitasking is defined as doing more than one thing at a time. Multitasking is really the engagement in individual and discrete tasks that are performed in succession. Research showed that students multitasked very often during courses. Researchers indicated that this was a problem especially for online teaching, because when students went online, they tended to multitask. Extant research indicated that digital multitasking in class harmed student performance. Multiple studies suggested that students who multitasked spent more time finishing their tasks and made more mistakes. Regardless of students’ gender or GPA, students who multitasked in class performed worse and got a lower grade than those who did not. However, little is known about how to change students’ digital multitasking behaviors. In this study, we used the transtheoretical model of behavior change to investigate how our pedagogical technique (CURE) changed students’ digital multitasking behaviors. Methodology: Using a course-based undergraduate research experience design, a new classroom intervention was designed and evaluated through a content analysis of pre- and post-intervention student reflections. As part of the course-based undergraduate research experience design, the students conducted a literature review, developed their own research questions, they analyzed experiment data, and presented results. This study evaluated the how teaching using a course-based undergraduate research experience contributed to student multitasking behavior change. Transtheoretical model of behavior change was used to investigate how our pedagogical technique changed students’ digital multitasking behaviors. Contribution: The paper described how teaching using a course-based undergraduate research experience can be used in practice. Further, it demonstrated the utility of this technique in changing student digital multitasking behaviors. This study contributed to constructivist approaches in education. Other unwanted student attitudes and behaviors can be changed using this approach to learning. Findings: As a result of CURE teaching, a majority of students observed the negative aspects of multitasking and intended to change their digital multitasking behaviors. Sixty-one percent of the participants experienced attitude changes, namely increased negative attitude towards multitasking in class. This is important because research found that while both students and instructors believed off-task technology use hinders learning, their views differed significantly, with more instructors than students feeling strongly that students’ use of technology in class is a problem. Moreover, our study showed that with teaching using CURE, it is possible to move the students on the ladder of change as quickly as within one semester (13 weeks). Seventy-one percent of the students reported moving to a higher stage of change post-intervention. Recommendations for Practitioners: Faculty wishing to curb student digital multitasking behaviors may conduct in-class experimentation with multitasking and have their students write a research report on their findings. Course-based undergraduate research experiences may make the effects of digital multitasking more apparent to the students. The students may become more aware of their own multitasking behaviors rather than doing them habitually. This technique is also recommended for those instructors who would like to introduce academic careers as a potential career option to their students. Recommendation for Researchers: Researchers should explore changing other unwanted undergraduate student behaviors with course-based undergraduate experiences. Researchers may use the transtheoretical model of change to evaluate the effectiveness of techniques used to change behaviors. Impact on Society: The negative outcomes of digital multitasking are not confined to the classroom. Digital multitasking impacts productivity in many domains. If techniques such as those used in this article become more common, changes in multitasking intentions could show broad improvements in productivity across many fields. Future Research: This paper constitutes a pilot study due to the small convenience sample that is used for the study. Future research should replicate this study with larger and randomized samples. Further investigation of the CURE technique can improve its effectiveness or reduce the instructor input while attaining the same behavioral changes.

The all-pervasive Internet has created serious problems, such as Internet overuse, which has triggered considerable debate over its relationship with addiction. To further explore its genetic susceptibilities and alternative explanations for Internet overuse, we proposed and evaluated four hypotheses, each based on existing knowledge of the biological bases of addiction, inattention, novelty-seeking, and harm-avoidance. Four genetic loci including DRD4 VNTR, DRD2 Taq1A, COMT Val158Met and 5-HTTLPR length polymorphisms were screened from seventy-three individuals. Our results showed that the DRD4 4R/4R individuals scored significantly higher than the 2R or 7R carriers in Internet Addiction Test (IAT). The 5-HTTLPR short/short males scored significantly higher in IAT than the long variant carriers. Bayesian analysis showed the most compatible hypothesis with the observed genetic results was based on attention (69.8%), whereas hypotheses based harm-avoidance (21.6%), novelty-seeking (7.8%) and addiction (0.9%) received little support. Our study suggests that carriers of alleles (DRD4 2R and 7R, 5-HTTLPR long) associated with inattentiveness are more likely to experience disrupted patterns and reduced durations of Internet use, protecting them from Internet overuse. Furthermore, our study suggests that Internet overuse should be categorized differently from addiction due to the lack of shared genetic contributions.

Non-expert scientists are frequently involved in research requiring data acquisition over large geographic areas. Despite mutual benefits for such “citizen science”, barriers also exist, including 1) difficulty maintaining user engagement with timely feedback, and 2) the challenge of providing non-experts with the means to generate reliable data. We have developed a system that addresses these barriers. Our technologies, KnoWare and InSpector, allow users to: collect reliable scientific measurements, map geo-tagged data, and intuitively visualize the results in real-time. KnoWare comprises a web portal and an iOS app with two core functions. First, users can generate scientific ‘queries’ that entail a call for information posed to a crowd with customized options for participant responses and viewing data. Second, users can respond to queries with their GPS-enabled mobile device, which results in their geo- and time-stamped responses populating a web-accessible map in real time. KnoWare can also interface with additional applications to diversify the types of data that can be reported. We demonstrate this capability with a second iOS app called InSpector that performs quantitative water quality measurements. When used in combina-tion, these technologies create a workflow to facilitate the collection, sharing and interpretation of scientific data by non-expert scientists.

The main aim of this paper is to provide a theoretically and empirically grounded discussion on IT-based organizational creativity support. This study attempts to answer the following questions: (1) what is the issue of organizational creativity and its IT-based support, (2) what is the demand for IT –based organizational creativity support; (3) what are the main determinants and barriers to IT-based organizational creativity support; and (4) what success factors are crucial for IT-based organizational creativity support. This paper presents the analysis results of a survey conducted in 25 selected organizations. The paper provides valuable information on the possibilities of IT applications in organizational creativity support as well as the associated success factors. It makes useful contribution to our better understanding of IT-based organizational creativity support issues.

Aim/Purpose: With information almost effortlessly created and spontaneously available, current progress in Information and Communication Technology (ICT) has led to the complication that information must be scrutinized for trustworthiness and provenance. Information systems must become provenance-aware to be satisfactory in accountability, reproducibility, and trustworthiness of data. Background: Multiple models for abstract representation of provenance have been proposed to describe entities, people, and activities involved in producing a piece of data, including the Open Provenance Model (OPM) and the World Wide Web Consortium. These models lack certain concepts necessary for specifying workflows and encoding the provenance of data products used and generated. Methodology: Without loss of generality, the focus of this paper is on OPM depiction of provenance in terms of a directed graph. We have redrawn several case studies in the framework of our proposed model in order to compare and evaluate it against OPM for representing these cases. Contribution: This paper offers an alternative flow-based diagrammatic language that can form a foundation for modeling of provenance. The model described here provides an (abstract) machine-like representation of provenance. Findings: The results suggest a viable alternative in the area of diagrammatic representation for provenance applications. Future Research: Future work will seek to achieve more accurate comparisons with current models in the field.

Aim/Purpose: The amount of information published has increased dramatically due to the information explosion. The issue of managing information as it expands at this rate lies in the development of information extraction technology that can turn unstructured data into organized data that is understandable and controllable by computers Background: The primary goal of named entity recognition (NER) is to extract named entities from amorphous materials and place them in pre-defined semantic classes. Methodology: In our work, we analyze various machine learning algorithms and implement K-NN which has been widely used in machine learning and remains one of the most popular methods to classify data. Contribution: To the researchers’ best knowledge, no published study has presented Named entity recognition for the Kikuyu language using a machine learning algorithm. This research will fill this gap by recognizing entities in the Kikuyu language. Findings: An evaluation was done by testing precision, recall, and F-measure. The experiment results demonstrate that using K-NN is effective in classification performance. Recommendation for Researchers: With enough training data, researchers could perform an experiment and check the learning curve with accuracy that compares to state of art NER. Future Research: Future studies may be done using unsupervised and semi-supervised learning algorithms for other resource-scarce languages.

Aim/Purpose: This review paper aims to unveil some underlying machine-learning classification algorithms used for political election predictions and how stack ensembles have been explored. Additionally, it examines the types of datasets available to researchers and presents the results they have achieved. Background: Predicting the outcomes of presidential elections has always been a significant aspect of political systems in numerous countries. Analysts and researchers examining political elections rely on existing datasets from various sources, including tweets, Facebook posts, and so forth to forecast future elections. However, these data sources often struggle to establish a direct correlation between voters and their voting patterns, primarily due to the manual nature of the voting process. Numerous factors influence election outcomes, including ethnicity, voter incentives, and campaign messages. The voting patterns of successors in regions of countries remain uncertain, and the reasons behind such patterns remain ambiguous. Methodology: The study examined a collection of articles obtained from Google Scholar, through search, focusing on the use of ensemble classifiers and machine learning classifiers and their application in predicting political elections through machine learning algorithms. Some specific keywords for the search include “ensemble classifier,” “political election prediction,” and “machine learning”, “stack ensemble”. Contribution: The study provides a broad and deep review of political election predictions through the use of machine learning algorithms and summarizes the major source of the dataset in the said analysis. Findings: Single classifiers have featured greatly in political election predictions, though ensemble classifiers have been used and have proven potent use in the said field is rather low. Recommendation for Researchers: The efficacy of stack classification algorithms can play a significant role in machine learning classification when modelled tactfully and is efficient in handling labelled datasets. however, runtime becomes a hindrance when the dataset grows larger with the increased number of base classifiers forming the stack. Future Research: There is the need to ensure a more comprehensive analysis, alternative data sources rather than depending largely on tweets, and explore ensemble machine learning classifiers in predicting political elections. Also, ensemble classification algorithms have indeed demonstrated superior performance when carefully chosen and combined.

This work demonstrates a hybrid deep learning (DL) model for lung cancer (LC) detection using CT images. Firstly, the input image is passed to the pre-processing stage, where the input image is filtered using a BF and the obtained filtered image is subjected to lung lobe segmentation, where segmentation is done using squeeze U-SegNet. Feature extraction is performed, where features including entropy with fuzzy local binary patterns (EFLBP), local optimal oriented pattern (LOOP), and grey level co-occurrence matrix (GLCM) features are mined. After completing the extracting of features, LC is detected utilising the hybrid efficient-ShuffleNet (HES-Net) method, wherein the HES-Net is established by the incorporation of EfficientNet and ShuffleNet. The presented HES-Net for LC detection is investigated for its performance concerning TNR, and TPR, and accuracy is established to have acquired values of 92.1%, 93.1%, and 91.3%.

Congcong FANG,Yun JIN,Guanlin CHEN,Yunfan ZHANG,Shidang LI,Yong MA,Yue XIE, Vol.E107-D, No.11, pp.1463-1467
Currently, an increasing number of tasks in speech emotion recognition rely on the analysis of both speech and text features. However, there remains a paucity of research exploring the potential of leveraging large language models like GPT-3 to enhance emotion recognition. In this investigation, we harness the power of the GPT-3 model to extract semantic information from transcribed texts, generating text modal features with a dimensionality of 1536. Subsequently, we perform feature fusion, combining the 1536-dimensional text features with 1188-dimensional acoustic features to yield comprehensive multi-modal recognition outcomes. Our findings reveal that the proposed method achieves a weighted accuracy of 79.62% across the four emotion categories in IEMOCAP, underscoring the considerable enhancement in emotion recognition accuracy facilitated by integrating large language models.
Publication Date: 2024/11/01

Keitaro NAKASAI,Shin KOMEDA,Masateru TSUNODA,Masayuki KASHIMA, Vol.E107-D, No.11, pp.1444-1448
To automatically measure the mental workload of developers, existing studies have used biometric measures such as brain waves and the heart rate. However, developers are often required to equip certain devices when measuring them, and can therefore be physically burdened. In this study, we evaluated the feasibility of non-contact biometric measures based on the nasal skin temperature (NST). In the experiment, the proposed biometric measures were more accurate than non-biometric measures.
Publication Date: 2024/11/01

Nan WU,Xiaocong LAI,Mei CHEN,Ying PAN, Vol.E107-D, No.11, pp.1433-1443
With the development of the Semantic Web, an increasing number of researchers are utilizing ontology technology to construct domain ontology. Since there is no unified construction standard, ontology heterogeneity occurs. The ontology matching method can fuse heterogeneous ontologies, which realizes the interoperability between knowledge and associates to more relevant semantic information. In the case of differences between ontologies, how to reduce false matching and unsuccessful matching is a critical problem to be solved. Moreover, as the number of ontologies increases, the semantic relationship between ontologies becomes increasingly complex. Nevertheless, the current methods that solely find the similarity of names between concepts are no longer sufficient. Consequently, this paper proposes an ontology matching method based on semantic association. Accurate matching pairs are discovered by existing semantic knowledge, and then the potential semantic associations between concepts are mined according to the characteristics of the contextual structure. The matching method can better carry out matching work based on reliable knowledge. In addition, this paper introduces a probabilistic logic repair method, which can detect and repair the conflict of matching results, to enhance the availability and reliability of matching results. The experimental results show that the proposed method effectively improves the quality of matching between ontologies and saves time on repairing incorrect matching pairs. Besides, compared with the existing ontology matching systems, the proposed method has better stability.
Publication Date: 2024/11/01

Qinghua WU,Weitong LI, Vol.E107-D, No.11, pp.1422-1432
Multi-focus image fusion involves combining partially focused images of the same scene to create an all-in-focus image. Aiming at the problems of existing multi-focus image fusion algorithms that the benchmark image is difficult to obtain and the convolutional neural network focuses too much on the local region, a fusion algorithm that combines local and global feature encoding is proposed. Initially, we devise two self-supervised image reconstruction tasks and train an encoder-decoder network through multi-task learning. Subsequently, within the encoder, we merge the dense connection module with the PS-ViT module, enabling the network to utilize local and global information during feature extraction. Finally, to enhance the overall efficiency of the model, distinct loss functions are applied to each task. To preserve the more robust features from the original images, spatial frequency is employed during the fusion stage to obtain the feature map of the fused image. Experimental results demonstrate that, in comparison to twelve other prominent algorithms, our method exhibits good fusion performance in objective evaluation. Ten of the selected twelve evaluation metrics show an improvement of more than 0.28%. Additionally, it presents superior visual effects subjectively.
Publication Date: 2024/11/01

Yuan LI,Tingting HU,Ryuji FUCHIKAMI,Takeshi IKENAGA, Vol.E107-D, No.11, pp.1396-1407
1 millisecond (1-ms) vision systems are gaining increasing attention in diverse fields like factory automation and robotics, as the ultra-low delay ensures seamless and timely responses. Superpixel segmentation is a pivotal preprocessing to reduce the number of image primitives for subsequent processing. Recently, there has been a growing emphasis on leveraging deep network-based algorithms to pursue superior performance and better integration into other deep network tasks. Superpixel Sampling Network (SSN) employs a deep network for feature generation and employs differentiable SLIC for superpixel generation. SSN achieves high performance with a small number of parameters. However, implementing SSN on FPGAs for ultra-low delay faces challenges due to the final layer’s aggregation of intermediate results. To address this limitation, this paper proposes an aggregated to pipelined structure for FPGA implementation. The final layer is decomposed into individual final layers for each intermediate result. This architectural adjustment eliminates the need for memory to store intermediate results. Concurrently, the proposed structure leverages decomposed layers to facilitate a pipelined structure with pixel streaming input to achieve ultra-low latency. To cooperate with the pipelined structure, layer-partitioned memory architecture is proposed. Each final layer has dedicated memory for storing superpixel center information, allowing values to be read and calculated from memory without conflicts. Calculation results of each final layer are accumulated, and the result of each pixel is obtained as the stream reaches the last layer. Evaluation results demonstrate that boundary recall and under-segmentation error remain comparable to SSN, with an average label consistency improvement of 0.035 over SSN. From a hardware performance perspective, the proposed system processes 1000 FPS images with a delay of 0.947 ms/frame.
Publication Date: 2024/11/01

Product innovation has become a crucial part of the sustainability of the coconut agro-industry in Indonesia, covering upstream and downstream sides. To overcome this challenge, it is necessary to create several model stages using a hybrid method that combines machine learning based on multiple criteria decision making and mass balance analysis. The research case study was conducted in Tembilahan district, Riau province, Indonesia, one of the primary coconut producers in Indonesia. The analysis results showed that potential products for domestic customers included coconut milk, coconut cooking oil, coconut chips, coconut jelly, coconut sugar, and virgin coconut oil. Furthermore, considering the experts, the most potential product to be developed was coconut sugar with a weight of 0.26. Prediction of coconut sugar demand reached 13,996,607 tons/year, requiring coconut sap as a raw material up to 97,976,249.

Evidence-based management has been widely advocated in management studies. It has great ambition: all manner of organizational problems are held to be amenable to an evidence-based approach. With such ambition, however, has come a certain narrowness which risks restricting our ability to understand the diversity of problems in management studies. Indeed, in the longer term, such narrowness may limit our capacity to engage with many real-life issues in organizations. Having repeatedly heard the case for evidence-based management, we invite readers to weigh up the case against. We also set out an alternative direction - one that promotes intellectual pluralism and flexibility, the value of multiple perspectives, openness, dialogue, and the questioning of basic assumptions. These considerations are the antithesis of an evidence-based approach, but central to a fully rounded management education.

Social enterprise has gained widespread acclaim as a tool for addressing social and environmental problems. Yet, because these organizations integrate the social welfare and commercial logics, they face the challenge of pursuing goals that frequently conflict with each other. Studies have begun to address how established social enterprises can manage these tensions, but we know little about how, why, and with what consequences social entrepreneurs mix competing logics as they create new organizations. To address this gap, we develop a theoretical model based in identity theory that helps to explain: (1) how the commercial and social welfare logics become relevant to entrepreneurship, (2) how different types of entrepreneurs perceive the tension between these logics, and (3) the implications this has for how entrepreneurs go about recognizing and developing social enterprise opportunities. Our approach responds to calls from organizational and entrepreneurship scholars to extend existing frameworks of opportunity recognition and development to better account for social enterprise creation.

In this paper, we use a practice-based wisdom perspective to address the challenges of managing competing logics in social enterprises. From previous work it is clear that a major task for social entrepreneurs is to manage the tension between social welfare and commercial logics. Although the social welfare logic and its related values and practices form the foundations of social enterprises, social entrepreneurs have also to ensure that their businesses are commercially sustainable making it necessary to engage with the commercial logic. To this end, we develop a curriculum matrix based on social practice wisdom to assist students to learn appropriate knowledge and skills, enact social entrepreneurship goals, and integrate competing logics in innovative and sustainable ways.

This rather difficult read introduces the programming language FSM and the programming platform DrRacket. The author asserts that it is a convenient platform to design and prove an automata-based software

KUALA LUMPUR: The shift towards subscription-based services is gaining traction in Malaysia, aligning with a broader global trend that redefines how consumers access products.

This model provides an appealing option for many Malaysians, particularly young families and newlyweds, who face rising living costs.

Offering high-quality appliances on a subscription basis eases the financial burden of ownership, allowing consumers to enjoy premium products without the pressure of a large upfront investment.

One notable brand offering subscription-based home appliance services is the South Korean brand, LG.

LG Malaysia product director of subscription business Hojin Jung said the introduction of the LG Rent Up Subscription in Malaysia is a natural progression of the company’s commitment to providing innovative and accessible solutions tailored to the evolving needs of modern consumers.

“LG Rent Up Subscription is inspired by our success with subscription models in South Korea, where we saw significant growth, driven by increasing demand for convenience and affordability.

“Recognising similar trends here, we noticed a growing interest in flexible ownership models in Malaysia, spurred by the need for more cost-effective solutions amidst rising living expenses and fuelled by shifting consumer preferences.

“Since its launch in March 2024, the market response has been encouraging. We have seen growing inquiries from customers who have signed up for our water purifier subscription model and are now exploring subscriptions for other high-demand appliances such as refrigerators, washing machines and TVs.

“This shift highlights a changing mindset in how Malaysians approach home appliance ownership – especially among younger, urban consumers who prioritise access over ownership, seeking premium products without the upfront financial commitment,” Hojin told SunBiz.

He said urbanisation and the desire for more sustainable, convenience-focused living have made subscription services an attractive option.

“By offering top-tier technology on a subscription basis, we make high-end living more accessible while emphasising affordability and environmental responsibility. LG’s Rent Up Subscription model meets Malaysians’ evolving needs, allowing them to enjoy premium technology without the burden of ownership,” he said.

Hojin said the subscription model is gaining popularity among young Malaysians, especially urban professionals and families facing high living costs and limited space.

This trend, he said, reflects a growing shift toward a ‘sharing economy,‘ where access to energy-efficient appliances without the financial strain of ownership is valued.

LG Rent Up Subscription’s launch saw a strong uptake in Kuala Lumpur and major cities, where 40% of tech-savvy millennials prefer renting to stay updated with technology affordably.

Elaborating on the model further, Hojin said that although subscription services share similarities across markets, the Malaysian context has distinct differences.

“In South Korea, for example, the rental model for water purifiers is well-established, with over 70% market penetration. Malaysia, meanwhile, is still in its early phase, but consumer awareness is rising quickly. Moreover, this trend is not isolated to Malaysia. LG is actively preparing to introduce the subscription model in other markets, including Taiwan and Thailand, by year-end.”

Touching on the vision for LG Rent Up in Malaysia, Hojin said the LG Rent Up Subscription is just the beginning of a transformative journey in how it engages with consumers in Malaysia.

“As we look ahead, we plan to expand our subscription offerings to include a wider array of smart home appliances and electronics, reflecting the growing demand for connected living solutions.

“Our vision for LG Rent Up Subscription is to enhance the customer experience by offering seamless integration with our LG ThinQ technology, which already empowers our appliances to be more intuitive and user-friendly. This will allow our customers to enjoy a smart, responsive lifestyle, further elevating the convenience and efficiency of their homes,” he explained.

Hojin said that as the subscription economy continues to evolve, particularly among tech-savvy and environmentally conscious consumers, LG Rent Up Subscription aims to play a pivotal role in making premium technology more accessible.

“Our ultimate goal is to foster a circular economy model in which subscribing to high-quality appliances reduces the financial burden on consumers and contributes to sustainability by extending product lifecycles and minimising waste.

“The more we enhance our subscription model, the more committed we are to making innovative technology more attainable. We ultimately aim to enrich the lives of our customers while promoting responsible consumption and environmental stewardship,” Hojin said.

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All 10 Nepali climbers are in good health and relaxing, says G-B govt spokesperson Faizullah Firaq

Widespread smuggling, tax evasion result in billions in lost revenue across key sectors

Is it possible to launch a website in 12 hours? You start out having lots of time ahead, yet at some point, the deadline creeps closer, and you realize you don’t have enough hours left to do the work.

This …

The post 12-hours deadline: launching a website on the run (based on Monstroid2) appeared first on Template Monster Help.

Supreme Court reviews a case concerning government jobs allocated through a statutory regulatory order (SRO)

The first stop of the Ride Hard Session Tour 2018 will taking place at the 5th of May, at the Trendsport hall in Basel. For the first stop they will host a chilled BMX jam with vouchers and goodies for tricks. If the weather will be nice, you can ride the Half-pipe, flatrails and curbs outside. Sounds good right?

All the best, your kunstform BMX Shop Team!

What:
Ride Hard Session Tour #1 Basel

When:
05 May 2018

Where:
Trendsport Basel
Uferstrasse 80
4057 Basel


More infos on Facebook.

For years my wife and I had to make due with trying to make Quicken work using a zero-based budget. While Quicken simply isn’t made for zero-based budgeting, we did find a cool hack that lets us keep track of our money in a way very similar to a zero-based budget. It’s kind of like […]

The post Zero-based budgeting with Quicken first appeared on Getting Finances Done.

An undated image shows Pakistan's baseball team poses with national flag Arab Classic Dubai 2024 championship. — APP/File

DUBAI: Pakistan’s baseball team clinched the Arab Classic Dubai 2024 championship as the team trampled the hosts United Arab Emirates with an...

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