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Toyota's internationally coordinated production system in Asia and its selection of supply bases in South America and South Africa highlights the significance of recognizing global network firms and the global hub-and-spoke logistics system that has been developed to meet their needs. This system underpins the expansion of container shipping, air freight and telecommunications. Recognition of Main Street, linking Europe, Asia and North America with cui-desacs in Africa, Australasia and Central and South America, provides a framework for examining the relative importance of the system's hubs and terminals across different modes and regions. This analysis provides the basis for identifying and ranking key regional logistics platforms in Northeast Asia and their attraction as headquarter sites for global network firms. Examining the logistical situation pertaining after the end of the Cold War in the early 1990s and a decade later is used to gauge progress towards regional economic integration in Northeast Asia.

Maturity models are a prospering approach to improving a company's processes and business process management (BPM) capabilities. In fact, the number of corresponding maturity models is so high that practitioners and scholars run the risk of losing track. This paper therefore aims to provide a systematic in‐depth review of BPM maturity models.

The paper follows the accepted research process for literature reviews. It analyzes a sample of ten BPM maturity models according to a framework of general design principles. The framework particularly focuses on the applicability and usefulness of maturity models.

The analyzed maturity models sufficiently address basic design principles as well as principles for a descriptive purpose of use. The design principles for a prescriptive use, however, are hardly met. Thus, BPM maturity models provide limited guidance for identifying desirable maturity levels and for implementing improvement measures.

The authors are confident that this review covers the majority of publicly available BPM maturity models. As the number of corresponding maturity models seems to be constantly growing, exhaustiveness can hardly be guaranteed. The study's results stimulate future research. Inter alia, adopters from industry require more elaborate support by means of ready‐to‐use and adaptable instruments for maturity assessment and improvement. The paper also reaffirms the need for maturity model consolidation in the field of BPM.

As existing literature reviews focus on process improvement or BPM in general, the paper's findings extend current knowledge. They also increase transparency. Its results provide guidance for scholars and practitioners involved in the design, enhancement, or application of BPM maturity models.

Initiator crimes, also known as near-repeat crimes, occur in places with known risk factors and vulnerabilities based on prior crime-related experiences or information. Consequently, the environment in which initiator crimes occur might be different from more general crime environments. This study aimed to analyse the differences between the environments of initiator crimes and general crimes, confirming the need for predicting initiator crimes.

We compared predictive models using data corresponding to initiator crimes and all residential burglaries without considering repetitive crime patterns as dependent variables. Using random forest and gradient boosting, representative ensemble models and predictive models were compared utilising various environmental factor data. Subsequently, we evaluated the performance of each predictive model to derive feature importance and partial dependence based on a highly predictive model.

By analysing environmental factors affecting overall residential burglary and initiator crimes, we observed notable differences in high-importance variables. Further analysis of the partial dependence of total residential burglary and initiator crimes based on these variables revealed distinct impacts on each crime. Moreover, initiator crimes took place in environments consistent with well-known theories in the field of environmental criminology.

Our findings indicate the possibility that results that do not appear through the existing theft crime prediction method will be identified in the initiator crime prediction model. Emphasising the importance of investigating the environments in which initiator crimes occur, this study underscores the potential of artificial intelligence (AI)-based approaches in creating a safe urban environment. By effectively preventing potential crimes, AI-driven prediction of initiator crimes can significantly contribute to enhancing urban safety.

While most corporate social responsibility (CSR) research has focused on its positive effects, the potential “dark side” of CSR has received scant attention. Grounded in vicarious moral licensing theory and insights from related literature, the current study examines how employees' perceptions of external CSR could result in unintentional negative consequences like unethical pro-organizational behavior via psychological entitlement. The study also investigates the direct and conditional effects of private self-awareness.

A two-wave survey of 609 full-time employees from various occupations was conducted to empirically test the hypotheses. Several techniques and remedies were applied to control the quality of the sample data and mitigate the effects of potential common method bias.

The results demonstrate that unethical pro-organizational behavior can be an unintentional negative outcome of perceived external CSR, and psychological entitlement mediates the relationship.

This work contributes to the moral licensing literature by examining vicarious moral licensing in the work domain. It offers several new and significant implications for research on CSR, psychological entitlement, and unethical pro-organizational behavior. The results suggest that managers should be mindful of unethical pro-organizational behavior as a potential negative consequence of external CSR engagement.

This study is among the first attempts to examine vicarious moral licensing in the work domain and investigates a largely neglected research area – the negative aspect of external CSR.

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the methodology was presented to convert customers' review data, which consisted of the text data (unstructured data), to the numerical data (structured data) by using a text mining algorithm “Global Vectors for Word Representation,” abbreviated as “GloVe”; additionally, the authors presented the methodology to deploy the numerical data for marketing strategies with eliminate-reduce-raise-create (ERRC) value factor analytics.

First, the authors defined the background, features and contents of fintech services based on a review of related literature review. Additionally, they examined business strategies, the importance of social media for fintech services and fintech technology trends based on the literature review. Next, they analyzed the similarity between fintech-related keywords, which represent the trends in fintech services, and the text data related to fintech corporations and their services posted on Facebook and Twitter, which are two of the most popular social media globally, during the period 2017–2019. The similarity was then quantified and categorized in terms of the representative global fintech companies and the status of each fintech service sector. Furthermore, the similarity was visualized, and value elements were rebuilt using ERRC strategy analytics.

This study is meaningful in that it quantifies the degree of similarity between customers' responses, experiences and expectations regarding the rapidly growing global fintech firms' services and trends in fintech services.

This study suggests a practical way to apply in business by providing a method for transforming unstructured text data into structured numerical data it is measurable. It is expected that this study can be used as the basis for exploring sustainable development strategies for the fintech industry.

This research aims to clarify the relationship between organizational identification and employees’ unethical pro-organizational behavior, which has been a topic of mixed findings in previous empirical studies. To address this issue, a meta-analytic review was conducted, focusing on the influence of key individual differences such as gender, age and organizational tenure on the relationship between organizational identification and unethical pro-organizational behavior.

The study utilizes large scholarly databases including Google Scholar, PsycINFO, Business Source Premier and ProQuest Dissertations to identify relevant studies. A total of 31 independent samples with a combined sample size of 8,861 participants were included in the analysis.

The results showed that the estimated average correlation between organizational identification and unethical pro-organizational behavior after corrected for measurement unreliability was 0.188 (p < 0.001, 95% [CI: 0.125, 0.251]). Gender demonstrated a significant moderating effect (estimate = 0.004, p < 0.05, 95% [CI: 0.000, 0.007]), suggesting that there is stronger association between organizational identification and unethical pro-organizational behavior among male participants. Neither age nor organizational tenure had significant effect on organizational identification-unethical pro-organizational behavior relations.

This study revealed that the organizational identification-unethical pro-organizational behavior link was positive, and the relationship was stronger among male participants than their female counterparts. Age and organizational tenure show no significant impact on unethical pro-organizational behavior. These contribute to The authors' understanding of organizational identification-unethical pro-organizational behavior relationship, as well as identifying its boundary conditions. The study suggests directions for future research and implications for managers and practitioners.

The purpose of this paper is to introduce Commercial Mobile Video Service Trial (TOEST) of Korea Telecom (KT), relaying experience related to the implementation of mobile video service for portable devices to libraries and information management organizations that are interested in this service.

Research data used were collected from internal materials such as unpublished project reports, RFI, RFP, etc. written throughout the process of implementing projects. The information also draws on the author's experience and involvement in TOEST trial between 2005 and 2007.

From the technical perspective, it was confirmed that technical advancements and environments that enable the implementation of mobile video service for portable devices have been fully established. The technical areas that need to be further improved are the advancements of battery capacity, low‐power consumption technology, and functional improvement of the I/O slot in portable devices.

TOEST provides only download type service for portable devices such as PDAs and PMPs. Streaming type service for mobile phones has been performed only for the purpose of internal tests.

For information management organizations and libraries, mobile video service for portable devices is cutting‐edge technical service that can provide new customer value to users. Also, it is possible to apply profit models from the commercial point of view.

The paper introduces various technical and environmental elements as specifically as possible, including practical things that we have experienced during the course of implementing mobile video service systems for portable devices. Experience in TOEST development would be helpful to information management organizations and libraries planning to provide mobile video service for portable devices.