Search

Purpose: Forced labour is one of the most exploitative practices in supply chains, generating serious human right abuses. The authors seek to understand how relationships for reducing forced labour are influenced by institutional logics. The emerging supply chain efforts of social enterprises offer particularly intriguing approaches, as their social mission can spur creative new approaches and reshape widely adopted management practices. Design/methodology/approach: The authors study supplier relationships in the smartphone industry and compare the evolving practices of two cases: the first, a growing novel social enterprise; and the second, a high-profile commercial firm that has adopted a progressive role in combating forced labour. Findings: The underlying institutional logic influenced each firm's willingness to act beyond its direct suppliers and to collaborate in flexible ways that create systematic change. Moreover, while both focal firms had clear, well-documented procedures related to forced labour, the integration, rather than decoupling, of forced labour and general supply chain policies provided a more effective way to reduce the risks of forced labour in social enterprises. Research limitations/implications: As authors' comparative case study approach may lack generalizability, future research is needed to broadly test their propositions. Practical implications: The paper identifies preconditions in terms of institutional logics to successfully reduce the risk of forced labour in supply chains. Originality/value: This paper discusses how social enterprises can provide a learning laboratory that enables commercial firms to identify options for supplier relationship improvement. [ABSTRACT FROM AUTHOR]

Smartphone positioning based on global navigation satellite systems is crucial for various applications, including navigation, emergency response, and augmented and virtual reality. Despite significant advancements, constraints on size, weight, power consumption, and cost still pose challenges, leading to degraded accuracy in challenging urban settings. To improve smartphone positioning accuracy, we introduce a novel framework that deeply couples a graph neural network (GNN) with a learnable backpropagation Kalman filter. This hybrid approach combines the strengths of both model-based and data-driven methods, enhancing adaptability in complex urban settings. We further augment the measurement modeling capabilities of the GNN with extended features, a novel edge creation technique, and an inductive graph learning framework. Additionally, we implement a unique backpropagation strategy that uses real-time positioning corrections to refine the performance of both the GNN and the learned Kalman filter. We validate our algorithm on real-world data sets collected via smartphone receivers in urban environments and demonstrate improved performance over existing model-based and learning-based approaches. [ABSTRACT FROM AUTHOR]

Prior research on catch-up strategies often provides insights from the technology-related perspective and ignores some non-technological factors. Through the multi-case study of China's smartphone industry, we develop a theoretical framework explaining how latecomer firms catch up through diverse strategic choices. We identify two strategic paths that latecomer firms follow to catch up and surpass the incumbents. One path is to explore new business opportunities via deep market insights and then combine them with building up product technologies. Another path is from product technology build-up to market insights exploration. Firms following this path usually start with building up essential technologies and act as fast followers for new market insights. Then, as they continue developing their technological strengths, these firms devote efforts to improving their ability to capture new market insights. This study challenges the 'first imitation, then innovation model' discussed in the literature and shows that latecomer firms can pursue cutting-edge innovations in their early activities. The research also shows that, unlike previous studies, the technology build-up is not the only path to help latecomers catch up and challenge incumbent leaders. [ABSTRACT FROM AUTHOR]

A theory of value pertinent to the contemporary iPhone era focuses on formal and informal labour circuits. This study extends this framework by examining a labour dispute in an iPhone factory near Bangalore, delving into its dissemination through media and the broader critical political economy surrounding the recent iPhone production in India. Furthermore, it incorporates a geographical perspective into the circuit framework to illustrate the movement of capital and labour in Bangalore, rekindling discussions on core–periphery dynamics in the context of capital and labour migration. Further, this research builds upon the typography of worker-generated content by illustrating a specific category of such content within the iPhone labour dispute. Utilising a critical political economy of media approach, this article aims to assess the broader implications of the updated framework and to open new avenues for research within the emerging field of information communication technologies, cultural production and labour. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Business Science (JOBS) / İşletme Bilimi Dergisi (JOBS) is the property of Journal of Business Science / Isletme Bilimi Dergisi (JOBS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of uncertain economic environments urban agglomerations play a crucial role in economic development, reshaping industrial chains and fostering inter-city cooperation. This study employs the Global Production Network (GPN) theory to enhance our understanding of how cities integrate into regions, emphasizing the often-overlooked governmental influence in strategic coupling processes. In examining the evolution of China's smartphone industry within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) this research categorizes 19,599 smartphone companies into five distinct groups. Through analyzing their spatial distribution and geographical linkage the study identifies four strategic coupling modes based on the localization of assets, considering spatial influence and technological complexity along horizontal and vertical dimensions. Structural and institutional elements within these modes are also explored. The research uncovers unique integration patterns among nine cities in the GBA's mobile industry, revealing distinct spatial clusters rooted in technological, resource and innovation factors. Crucially, local policies play a pivotal role. Cities such as Shenzhen and Dongguan emerge as technology hubs, contrasting with Foshan and Zhongshan, which leverage resource advantages. The spatial impact, contingent on specific assets, underscores the necessity for nuanced top-down coupling methods in regional development. Moreover, the study emphasizes the significance of nurturing innovation links, not only between leading companies but also among midstream and downstream enterprises, enhancing cities' strategic coupling capabilities. [ABSTRACT FROM AUTHOR]

It has been challenging for firms to effectively manage demand when they release products of one generation after another one. Motivated by the observations from the smartphone industry, this paper investigates the effectiveness of two demand management strategies in the presence of a product rollover: the upgrade program and price markdown policy. Under an upgrade program, a firm allows customers to upgrade their on‐hand product to a new generation product that will be released in a future time. Under a markdown pricing policy, the firm offers a discount for the currently available product so as to induce waiting customers to make immediate purchases. The two demand management strategies target different groups of customers and have distinct impacts on customers' choices. Starting from the time‐varying choice behavior of a heterogeneous group of customers, we study the optimal pricing decisions involved in the two strategies. Specifically, when customers are myopic in the sense that they only make a one‐time purchasing decision upon arrival, we show that the firm should offer the upgrade program only when the innovation level of the new product is relatively high, and the firm's optimal upgrade price can increase over time. Generally, the firm should offer the upgrade program during the early selling period and adopt markdown pricing as the release date of the new product approaches. Numerical experiments reveal that the dynamic upgrade program and markdown pricing policies can help improve profit significantly. When customers are strategic in the sense that they can monitor the selling prices and make dynamic purchasing decisions until they buy a unit of product, we examine two coping strategies that a firm can adopt, and investigate how the strategic monitoring behavior may influence a firm's optimal selling decisions and profit. [ABSTRACT FROM AUTHOR]

Unprecedented growth and prevalent adoption of the Android Operating System (OS) have triggered a substantial transformation, not only within the smartphone industry but across various categories of intelligent devices. These intelligent devices store a wealth of sensitive data, making them enticing targets for malicious individuals who create harmful Android applications to steal this data for malicious purposes. While numerous Android malware detection methods have been proposed, the exponential growth in sophisticated and malicious Android apps presents an unprecedented challenge to existing detection techniques. Some of the researchers have attempted to classify malicious Android applications into families through static analysis of applications but most of them are evaluated on applications of previous API levels. This paper introduces a novel dataset compromising of 2019 to 2021 applications and proposes a Deep Learning based Malware Detection and Family Classification method (DeepMDFC) to detect and classify emerging malicious Android applications through static analysis and deep Artificial Neural Networks. Experimental findings indicate that DeepMDFC surpasses standard machine learning algorithms, achieving accuracy rates of 99.3% and 96.7% for Android malware detection and classification, respectively, with a limited size feature set. The performance of DeepMDFC is also assessed using the benchmark dataset (DREBIN) and results showed that DeepMDFC surpasses these methods in terms of performance. Furthermore, it leverages the proposed dataset to construct a prediction model that adeptly identifies malicious Android applications from both the years 2022 and 2023. This process the potency and resilience of DeepMDFC against emerging Android applications. [ABSTRACT FROM AUTHOR]

This article provides an overview of the economic relationship between Japan and India, with a focus on India's growing economy and its potential for further growth. India has experienced significant economic growth and is expected to become the world's third-largest economy in the near future. The article highlights India's efforts to boost its manufacturing sector through initiatives like "Make in India 2.0" and the Production Linked Incentive (PLI) scheme. It also discusses the rapid growth of India's electronics industry, particularly in mobile phone production, and its efforts to develop the semiconductor industry. The article acknowledges the geopolitical risks and challenges that India faces in its economic growth. It further explores the strengthening relationship between Japan and India, particularly in the areas of national security, economy, and infrastructure development. Specific initiatives include collaboration in building resilient semiconductor supply chains, investment by Japanese companies in India's manufacturing sector, and Japan's contribution to India's infrastructure development through official development assistance. The article emphasizes the potential for further expansion of the bilateral relationship and the importance of fostering mutual understanding through people-to-people exchanges. [Extracted from the article]

This article provides an overview of the Southeast Asian economy in 2023 and its prospects for 2024. It discusses the challenges faced by ASEAN economies, such as monetary tightening, a sluggish Chinese economy, and disruptions in global supply chains. Despite these challenges, the region has shown resilience due to sound fiscal and monetary policies and structural advantages. The article also highlights the effects of geopolitical strains and the fragmentation of globalization. It emphasizes the advantages of ASEAN economies, including low operating costs, political stability, and attractive long-term fundamentals. The region is also enhancing digital connectivity and upgrading factories through digital solutions. While there are potential risks, such as the Middle East crisis and the US-China power struggle, ASEAN can expect a better 2024 with effective policy support. [Extracted from the article]

This study presents a comprehensive overview of the smartphone charging technology evolution from its inception to the present day and its future trends. It also examines the impacts of government regulations and industry standards on smartphone technology development. This review also focuses on topology and architecture comparisons. The suitability of each solution is closely examined based on the complexity, size, efficiency, and flexibility of the system. This review provides a valuable framework for the development of next-generation power architectures and topologies for mobile devices. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study how brand owners and users enhance brand bond with three objectives. First, brand owners' effort (BOE) to exercise care, innovate frequently and differentiate their brands enhances users' bond with the brand. Second, brand users' competence (BUC) in their knowledge and experience with the brand's reputation, value and service quality improves brand bond. Third, BOE significantly enhances BUC. Design/methodology/approach: This study proposed an integrative model with new concepts and tested it with 2,135 young Chinese consumers using global smartphone brands. Results are drawn from structural equation modeling and comparisons between stakeholders and among smartphone brands. Findings: The results show that BOE and BUC are significant and equally effective at enhancing brand bond. BOE also shows a significantly stronger effect on BUC than on brand bond. The temporal comparison between 2015 and 2018 confirms the changing reality of the smartphone world. As for brand comparison, young consumers perceive that iPhone differentiates itself from Huawei and Samsung rivals in terms of BOE and BUC on brand bond. However, none of these brands show significant differences in terms of BOE effect on BUC. Research limitations/implications: Please see detail in the Conclusion and Discussions. Practical implications: Please see detail in the Conclusion and Discussions. Social implications: Please see detail in the Conclusion and Discussions. Originality/value: This study introduced a validated model with new concepts based on the global smartphone industry, perceived by young Chinese consumers. The results prove that it takes both the owners and users together to contribute to the brand bond, but brand owners' role on BUC is more significant. [ABSTRACT FROM AUTHOR]

• A green disposal method for waste smartphone protective film was developed. • Hydrolysis of PAA to alcohol products favored the separation of PAA from PET. • PAA removal efficiency was over 97.2 % during continuous bench-scale test. • A net profit margin of 647 % for the second year was predicted. • Pyrolysis product of waste PAA showed adsorption capacity toward organics. The manufacture and obsolescence of smartphones produce numerous waste plastic accessories (e.g., waste smartphone protective film (WSPF)), possessing immense potential for recycling. However, available recycling technologies have limitations such as substrate damage and secondary pollutant generation. The present study aimed to develop a green disposal method that not only recycled polyethylene terephthalate (PET) from WSPF, but also reused the stripped polyacrylate (PAA) adhesive as an adsorbent to reduce solid waste generation. When the WSPF was treated in 1 mol/L NaOH solution at 90 °C, the PAA hydrolyzed to two main by-products of 1-butanol and 2-ethylhexanol, weakening the binding strength between PAA and PET and then efficient separation of them. Further bench-scale test revealed that over 97.2% of detachment efficiency toward PAA was achieved during continuous treatment of 17 batches of WSPF (200 g for each) without supplement of NaOH and generation of wastewater. Meanwhile, the economic evaluation indicated that the recycling method would generate a net profit margin of 647% for the second year without considering the incurrence of new cost and input. Additionally, the pyrolysis of waste PAA enabled its conversion into potential adsorbent, which showed 2 to 4 times enhanced adsorption capacity toward styrene and ethyl acetate after modification with NaOH solution. This study provides a green method for recycling waste plastics and inspires a referable solution for solid waste treatment in the smartphone industry. [Display omitted] [ABSTRACT FROM AUTHOR]

The study explores the direct and mediated impacts of customers' perception of purchase budget (BGT) on purchase intention (PIT) through perceived quality (PPQ), perceived price (PPR), and perceived benefit (PB) in a cross-country setting to understand BGT's role in predicting customer purchase intention in smartphone selling through international online shopping platforms. An online survey was conducted in Kenya, France, and the United States to gather data from 429 consumers who had recently purchased one or more smartphones through international online shopping platforms. SmartPLS-4 was used to test the hypotheses. Results for the entire sample showed a significantly positive mediating role of PPR and PPQ between BGT and PIT. However, the mediating roles of PPQ and PB were not significant in the samples from Kenya, France, and the United States. The results also showed that PPR plays a significant and positive mediating role between BGT and PIT in samples from Kenya, France, the United States, and overall. However, the direct relationships between BGT and PPQ, PPR, and PB are shown to be negatively significant. [ABSTRACT FROM AUTHOR]

Android malware has exploded in popularity in recent years, due to the platform's dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model's wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model. [ABSTRACT FROM AUTHOR]

Although the literature on network effects has focused on single-network firms, many industries feature multinetwork firms that play more complex dynamic pricing games. In this paper, we estimate the network effect at the smartphone operating system (OS) level and study multi-OS telecommunication carriers' dynamic pricing strategies in an oligopolistic setting, using data on the U.S. smartphone industry. We find a positive OS network effect. Counterfactual analysis indicates that if the carriers were single-OS sellers, they would increase the phone prices of large OSs and lower the prices of small OSs, which reduces the consumer surplus by $6.99 billion. Further analyses show that the multi-OS carriers choose lower prices for large OSs than for small OSs because of their preference for OS concentration. This paper was accepted by Eric Anderson, marketing. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72203217, 71803205, and 72192803] and the fund for building world-class universities (disciplines) of Renmin University of China. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4530. [ABSTRACT FROM AUTHOR]

Introduction: Consideration of educational system quality in the context of the learning management system has increased during the pandemic period. An inconsistent finding concerning the influence of educational system quality on satisfaction has been identified. To fill this gap in the existing literature, this study aims to extend the educational system quality scale and examine its influence on students' satisfaction. Methods: Based on an intensive literature review step, device flexibility was proposed as an extended indicator. To validate and examine the proposed hypothesis, this study employed the quantitative method of PLS-SEM. Data were collected from 90 students who actively used learning management systems. Results: Our findings showed that device flexibility is valid and reliable as an educational system quality indicator. Besides, our proposed hypothesis is also confirmed. Through the structural model assessment, the influence of educational system quality on students' satisfaction is found to be significant. Conclusion and suggestion: Device flexibility has been proven as an educational system quality indicator. In order to maintain students' satisfaction, system developers are suggested to keep improving learning management system applications, primarily on smartphone devices. [ABSTRACT FROM AUTHOR]

Despite the growing impact of smartphone use on countries' economies, the literature has rarely investigated the link between economic context and smartphone purchase trends. Based on 20,556 smartphones sold from a Cross-Border E-Commerce (CBEC) platform, the study reveals that relationships between GDP per capita and Smartphone Choice Preferences (SCP) as well as Purchase Quantities (PUR) are direct and partially mediated by Price (PRI), Read-Only Memory (ROM), and Random-Access Memory (RAM). That means that the economic context highlighted by the GDP plays a substantial role in smartphone choices and purchases. The study suggests that e-sellers and smartphone brands should adapt their marketing and manufacturing strategies to the countries' economic contexts to leverage the fearless competition in the smartphone industry. [ABSTRACT FROM AUTHOR]

The rapid growth in the technological advancements of the smartphone industry has classified contemporary smartphones as a low-cost and high quality indoor positioning tools requiring no additional infrastructure or equipment. In recent years, the fine time measurement (FTM) protocol, achieved through the Wi-Fi round trip time (RTT) observable, available in the most recent models, has gained the interest of many research teams worldwide, especially those concerned with indoor localization problems. However, as the Wi-Fi RTT technology is still new, there is a limited number of studies addressing its potential and limitations relative to the positioning problem. This paper presents an investigation and performance evaluation of Wi-Fi RTT capability with a focus on range quality assessment. A set of experimental tests was carried out, considering 1D and 2D space, operating different smartphone devices at various operational settings and observation conditions. Furthermore, in order to address device-dependent and other type of biases in the raw ranges, alternative correction models were developed and tested. The obtained results indicate that Wi-Fi RTT is a promising technology capable of achieving a meter-level accuracy for ranges both in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, subject to suitable corrections identification and adaptation. From 1D ranging tests, an average mean absolute error (MAE) of 0.85 m and 1.24 m is achieved, for LOS and NLOS conditions, respectively, for 80% of the validation sample data. In 2D-space ranging tests, an average root mean square error (RMSE) of 1.1m is accomplished across the different devices. Furthermore, the analysis has shown that the selection of the bandwidth and the initiator–responder pair are crucial for the correction model selection, whilst knowledge of the type of operating environment (LOS and/or NLOS) can further contribute to Wi-Fi RTT range performance enhancement. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Herein, a ratiometric fluorescence aptasensor was established for zearalenone (ZEN) detection based on fluorescence resonance energy transfer (FRET) between aptamer-modified CdTe quantum dots (QDs) as donor and gold nanoparticles (AuNPs) as acceptor. The fluorescence of CdTe QDs quenched by AuNPs based on FRET, while Si QDs with blue fluorescence as reference. The aptamer-modified CdTe QDs were adsorbed to ZEN in the presence of ZEN, and the distance between the energy receptor and the donor increased, which prevented the FRET and led to the fluorescence recovering of CdTe QDs. The aptasensor exhibited a limit of detection of 3.5 pg/mL with a linear range of 0.01–100 ng/mL. In addition, a portable detection device was constructed by integrating with smartphone for point-of-care testing (POCT) of ZEN with satisfactory results, which could provide a promising application for visual POCT of ZEN in cereals. • A FRET-based ratiometric aptasensor was developed for detection of ZEN. • The aptasensor exhibited a low LOD and a wide linear range. • Visualization and point-of-care testing of ZEN. [ABSTRACT FROM AUTHOR]

Innovation generates significant benefits for business, the economy, and society as a whole. An innovative product brings significant benefits and improved features to the market. This study aims to explore the effect of innovation characteristics on consumer resistance to innovation in the Smartphone industry. The data have been collected from 310 university students in Pakistan. The findings revealed that factors of innovation characteristics (relative advantage, perceived risk, and e‐word of mouth) have significant relationships with consumer resistance to innovation. Consumer innovativeness has shown the moderating effect on the relationships between innovation characteristics and consumer resistance to innovation. Limitations of the study, implications for theory and practice, and future research directions have been discussed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to identify and characterize the role of both original equipment manufacturer (OEM) and module supplier (MS) knowledge in the smartphone industry. In particular, this study aims to evaluate which of the two actors possesses the knowledge that has the greatest impact on the market satisfaction. Design/methodology/approach: This study explores and combines the concepts of modularity and knowledge management by investigating the patent portfolio of 16 leading smartphone OEMs and 144 MSs. The applied methodology is based on the content analysis of patent data to extract information on both OEM's and MS's component knowledge. Findings: The results show that, although its components are purchased from external MSs, the OEM should preserve both a general and specific concentration of component knowledge, as well as on the end product, to achieve a greater market satisfaction. Moreover, a positive direct relationship was found for the MS between the general concentration of component knowledge and the market satisfaction. Originality/value: The novelty of this study is to segment the knowledge of both the OEM and the MS on multiple levels. To the best of the authors' knowledge, this is one of the first studies that investigates the end product and component knowledge of both actors by filtering patent data using text-mining techniques. The originality of this work is to intercept the relationship between the different shades of knowledge of each actor and the market satisfaction. [ABSTRACT FROM AUTHOR]